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Career Path - Data Consultant

Analyze data, Develop data strategy, Practice data management tools & technologies, Build & implement data systems, Monitor data quality & performance
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Course Duration: 500 Hours
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The Data Consultant Career Path Program by Uplatz consists of 18 courses that will help you become a top consultant in technology and data.

1).Business Intelligence and Data Analytics

2).Cloud Computing Basics

3).Python Programming

4).Data Visualization in Python

5).R Programming

6).Data Visualization in R

7).Power BI

8).Power BI (basic to advanced)

9).Tableau

10).Tableau (comprehensive)

11).SAS Business Intelligence

12).Talend

13).SQL Programming with MySQL

14).Microsoft Excel

15).Google Sheets

16).Project Management Fundamentals

17).Microsoft Project (basic to advanced)

18).Leadership and Management

 

A data consultant is a professional who provides guidance and support to organizations in managing, analyzing, and interpreting their data to drive business decisions. They have expertise in data management, data analysis, and data visualization, and they work with businesses to help them make sense of their data.

 

Data consultants may be hired on a project basis or as a long-term partner to help organizations with their data strategy, data architecture, data governance, data quality, data security, and data analytics. They may also help organizations with the selection, implementation, and customization of data-related software and tools.

 

In order to be a successful data consultant, one must have strong analytical and problem-solving skills, as well as excellent communication and interpersonal skills. They should be proficient in data management technologies and programming languages, such as SQL, Python, and R, and should have a deep understanding of data analysis techniques and statistical methods. Additionally, they should stay up-to-date with the latest trends and developments in the field of data management and analytics.

 

A data consultant needs a blend of technical, analytical, and interpersonal skills. Key skills include:

1).Data Analysis: Proficiency in statistical analysis, data modeling, and data visualization techniques.

2).Programming: Strong skills in programming languages like R, Python, SQL, and familiarity with data tools like Excel, Tableau, and Power BI.

3).Database Management: Knowledge of database systems, data warehousing, and data architecture.

4).Business Acumen: Understanding of business processes and the ability to translate business requirements into data-driven solutions.

5).Problem-Solving: Strong analytical and critical thinking skills to identify issues and develop effective solutions.

6).Communication: Excellent verbal and written communication skills to convey complex data insights to non-technical stakeholders.

7).Project Management: Ability to manage projects, meet deadlines, and work with cross-functional teams.

8).Ethics and Privacy: Understanding of data privacy laws and ethical considerations in data handling and analysis.

 

This Data Consultant career track course will help you become a top Data/Technology Consultant and get hired by premium consulting and technology firms.

 

Course/Topic 1 - Business Intelligence and Data Analytics - all lectures

  • In this lecture session we discuss about Bi concepts, examples and application of business intelligence and data analytics and also cover other concepts of BI.

    • 14:48

  • In this lecture session we learn about basic concepts of BI and also cover factors of business intelligence in brief.

    • 19:22

  • In this lecture session we learn about data warehouse data access and data dashboarding and also cover presentation in BI.

    • 24:10

  • In this lecture session we learn about product database, advertise database and customer demographic database and also cover data analyst concepts.

    • 19:54

  • In this lecture session we learn about basic introduction of business intelligence and also cover factors of business intelligence in brief.

    • 31:10

  • In this lecture session we learn about introduction of predictive modeling and also cover functions of predictive modeling in brief.

    • 1:05:08

  • In this lecture session we learn about data related to customer services and also talk about customer relation databases in brief.

    • 32:37

  • In this lecture session we learn about introduction of NoSQL and also cover basic functions of NoSQL in business intelligence.

    • 33:46

  • In this lecture session we learn about graph stores and also talk about the advantages and disadvantages of graph stores in BI.

    • 25:52

  • In this lecture session we learn about hierarchical clustering in business intelligence and also talk about clustering factors in BI.

    • 29:58

  • In this lecture session we learn about introduction of salesforce in business intelligence and also talk about some basic uses of salesforce.

    • 34:25

  • In this lecture session we learn about introduction to NLP and also cover what is natural language processing in artificial intelligence.

    • 18:30

  • In this lecture session we learn about natural language processing speech to text conversion and also cover the importance of natural language processing.

    • 25:22

  • In this lecture session we learn about introduction of apache server in business intelligence and also talk about basics of apache server.

    • 44:24

  • In this lecture session we learn about deep drive into business intelligence and also talk about factors or deep drive in business intelligence.

    • 30:54

  • In this lecture session we learn about data warehousing in business intelligence and data analytics and also talk about factors and features of data warehousing.

    • 39:54

  • In this lecture session we learn about types of data in business intelligence and also talk about different types of data in BI.

    • 25:07

  • In this lecture session we learn about mobile BI and also talk about open source BI software replacing vendor offering.

    • 39:18

  • In this lecture session we learn about real time BI in business intelligence and also talk about factors of real time BI in brief.

    • 1:35:17

  • In this lecture session we learn about data analytics comprehensively and also talk about functions of data analytics.

    • 23:43

  • In this lecture session we talk about data analytics vs business analytics and also talk about the importance of data analytics.

    • 41:04

  • In this lecture session we learn about Embedded analytics and also talk about functions of Embedded analytics in data analytics.

    • 1:02:55

  • In this lecture session we learn about collection analytics and also cover the importance of collection analytics.

    • 59:03

  • In this lecture session we learn about survival analytics and also cover duration analytics in brief.

    • 29:35

  • In this lecture session we learn about machine learning techniques and also cover the importance and factors of machine learning techniques in business intelligence.

    • 37:34

  • In this lecture session we learn about geospatial predictive analytics and also talk about functions of geospatial predictive analytics in business intelligence.

    • 1:01:31

  • In this lecture session we learn about cohort analysis in data analyst and we also cover functions and importance of cohort analysis.

    • 21:36

  • In this lecture session we learn about data mining in business intelligence and also talk about data mining functions and why we need data mining in business intelligence.

    • 45:40

  • In these lecture sessions we learn about anomaly detection and also talk about functions of anomaly detection in brief.

    • 1:00:36

  • In these lecture sessions we learn about statistically sound association and also talk about factors of statistically sound association in business intelligence.

    • 31:29

  • In this lecture session we learn about cluster analysis. We’ll cover all types of cluster analysis in brief and also cover the importance of cluster analysis in business analysis.

    • 36:21

  • In this lecture session we learn about DBSCAN in business intelligence and also talk about DBSCAN functions and importance.

    • 59:58

  • In this lecture session we learn about regression models in business intelligence and also talk about the function of regression models.

    • 31:57

  • In this lecture session we learn about extraction based summarization in business intelligence and also cover all types of summarization in data analyst.

    • 10:57

  • In this lecture session we learn about machine learning in BI and also talk about factors and importance of machine learning in brief.

    • 1:00:50

  • In this lecture session we learn about machine learning vs BI we also discuss the basic difference between machine learning and business intelligence.

    • 1:15:37

  • In this lecture session we learn about how ml can make BI better and also talk about ml basic functions.

    • 1:18:01

  • In this lecture session we learn about data warehousing and also talk about how we manage data warehousing in business intelligence.

    • 18:28

  • In this lecture session we learn about data warehousing in business intelligence and data analytics and also talk about factors and features of data warehousing.

    • 29:22

  • In this lecture session we learn about data mart in business intelligence and also talk about data mart function.

    • 32:40

  • In this lecture session we learn about data dimensions in business intelligence and also cover all types of data dimension in BI.

    • 30:31

  • In this lecture session we learn about data dimension in business intelligence and also cover functions and importance of data dimension.

    • 24:02

  • In this lecture session we learn about data vault modeling in business intelligence and also cover different types of vault modeling in brief.

    • 29:14

  • In this lecture session we learn about links and satellites and also cover the importance and factors of links and satellites in business intelligence.

    • 28:59

Course/Topic 2 - Cloud Computing Basics - all lectures

  • In this lecture session we learn about cloud computing, which means storing and accessing data over the internet instead of a hard disk. It is defined as a service that provides users to work over the internet.

    • 38:26

  • In this lecture session we learn about cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale.

    • 30:33

  • In this lecture session we learn about Cloud computing is a general term for anything that involves delivering hosted services over the internet. These services are divided into three main categories or types of cloud computing.

    • 33:14

  • In this tutorial we learn about the importance of cloud computing can be found in using services like Google Drive and Apple iCloud. The use of these services allows documents, contacts, pictures, and a whole lot more online.

    • 32:19

Course/Topic 3 - Python Programming - all lectures

  • In this lecture session we learn about introduction to python programming for beginners and also talk about features of python programming.

    • 10:21

  • In this lecture session we learn about basic elements of python in python programming and also talk about features of elements of python.

    • 19:37

  • In this lecture session we learn about installation of python in your system and also talk about the best way of installation of python for beginners.

    • 13:18

  • In this lecture session we learn about input and output statements in python programming and also talk about features of input and output statements.

    • 24:05

  • In this lecture session we learn about data types in python programming and also talk about all the data types in python programming.

    • 23:05

  • In this lecture session we learn about operators in python and also talk about how we use operators in python programming.

    • 47:07

  • In this lecture session we learn about different types of operators in python programming and also talk about features of operators in python.

    • 29:47

  • In this lecture session we learn about type conversion in python programming and also talk about features of type conversion in python.

    • 23:39

  • In this lecture session we learn about basic programming in python programming for beginners.

    • 15:56

  • In this lecture session we learn about features of basic programming in python and also talk about the importance of programming in python.

    • 05:13

  • In this lecture session we learn about math modules in python programming and also talk about features of math modules in python.

    • 26:43

  • In this lecture session we learn about conditional statements in python and also talk about conditional statements in python programming.

    • 28:24

  • In this lecture session we talk about basic examples of conditional statements in python.

    • 19:27

  • In this lecture session we learn about greater and less then conditional statements in python programming.

    • 13:39

  • In this lecture session we learn about nested IF Else statements and also talk about features of nested IF else statements.

    • 11:04

  • In this lecture session we learn about looping in python in programming for beginners and also talk about looping in python.

    • 25:06

  • In this lecture session we learn about break and continue keywords and also talk about features of break continue keywords.

    • 20:48

  • In this lecture session we learn about prime number programs in python and also talk about functions of prime number programs in python.

    • 17:31

  • In this lecture session we learn about while loop in python programming and also talk about features of while loop in python.

    • 35:35

  • In this lecture session we learn about nested For loop in python programming and also talk about features of nested For loop.

    • 12:34

  • In this lecture session we learn about features of nested for loop in python and also talk about the importance of nested For loop in python.

    • 12:49

  • In this lecture session we learn about functions in python and also talk about different types of functions in pythons.

    • 19:28

  • In this lecture session we learn about passing arguments to functions in python programming and also talk about features of passing arguments to functions

    • 08:59

  • In this lecture session we learn about return keywords in python and also talk about features of return keywords in python.

    • 12:16

  • In this lecture session we learn about calling a function in python programming and also talk about calling a function.

    • 15:07

  • In this lecture session we learn about factors of calling a function in python programming and also talk about features of calling a function.

    • 20:17

  • In this lecture session we learn about a program to swap 2 numbers using calling a function in python programming.

    • 19:27

  • In this lecture session we learn about functions of arbitrary arguments in python programming and also talk about features of arbitrary arguments.

    • 10:34

  • In this lecture session we learn about functions keywords arguments in python programming and also talk about features of keyword arguments.

    • 06:55

  • In this lecture session we learn about functions default arguments in python programming and also talk about features of default argument.

    • 06:57

  • In this lecture session we learn about global and local variables in python programming and also talk about features of global and local variables.

    • 19:37

  • In this lecture session we learn about global and local keywords and also talk about features of global and local keywords.

    • 10:44

  • In this lecture session we learn about strings in python programming and also talk about features of string in python.

    • 17:42

  • In this lecture session we learn about string methods in python programming and also talk about features of string methods in python.

    • 21:53

  • In this lecture session we learn about string functions in python and also talk about features of strings functions in python.

    • 28:02

  • In this lecture session we learn about string indexing in python programming and also talk about features of string indexing in python programming.

    • 13:51

  • In this lecture session we learn about introduction of lists in python programming and also talk about features of introduction to lists.

    • 06:31

  • In this lecture session we learn about basics of lists python programming and also talk about features of basics of lists in python.

    • 33:09

  • In this lecture session we learn about list methods and also talk about features of list method python programming.

    • 32:43

  • In this lecture session we learn about linear search on list and also talk about features of linear search on list in brief.

    • 23:20

  • In this lecture session we learn about the biggest and smallest number of the list and also talk about features of MAX and Min in a list.

    • 14:40

  • In this lecture session we learn about the difference between 2 lists in python programming and also talk about features of 2 lists.

    • 13:22

  • In this lecture session we learn about tuples in python programming and also talk about tuples in python programming.

    • 20:19

  • In this lecture session we learn about introduction to sets in python and also talk about functions of introduction to sets in python.

    • 32:43

  • In this lecture session we learn about set operations in python programming and also talk about features of set operation in brief.

    • 26:56

  • In this lecture session we learn about set examples and also talk about features set examples.

    • 11:05

  • In this lecture session we learn about introduction to dictionaries in python programming and also talk about featured dictionaries.

    • 14:47

  • In this lecture session we learn about creating and updating dictionaries in python programming and also talk about features of creating and updating dictionaries.

    • 32:49

  • In this lecture session we learn about deleting items in a dictionary in python programming and also talk about features of deleting items in a dictionary.

    • 08:06

  • In this lecture session we learn about values and items in a dictionary in python programming and also talk about features of values and items in the dictionary.

    • 13:14

  • In this lecture session we learn about dictionary methods in python programming and also talk about features of dictionary methods.

    • 18:46

  • In this lecture session we learn about built in methods in python programming and also talk about features of built in methods in python.

    • 20:25

  • In this lecture session we learn about lambda functions and also talk about features of lambda function in python programming.

    • 15:29

  • In this lecture session we learn about file handling in python programming and also also talk about the importance of file handling in python.

    • 15:58

  • In this lecture session we learn about file handling in python programming and also talk about features of file handling in python.

    • 36:13

  • In this lecture session we learn about exception handling in python and also talk about features of exception handling in python.

    • 08:46

  • In this lecture session we learn about exception handling examples in python programming.

    • 25:04

  • In this lecture session we learn about python programs in python programming and also talk about features of python programs

    • 18:40

  • In this lecture session we learn about the program of printing odd numbers in python programming and also talk about the best way of printing.

    • 10:46

  • In this lecture session we learn about counting the number of vowels and consonants in a string and also talk about features of these programs.

    • 21:38

  • In this lecture session we learn about python programs of swapping two numbers in a list by taking indexes as parameters.

    • 14:08

  • In this lecture session we learn about bubble sort and also talk about features of bubble sort in brief.

    • 35:36

  • In this lecture session we learn about operator precedence in python and also talk about features of operator precedence in python.

    • 14:51

  • In this lecture session we learn about operator precedence in python and also talk about features of operator precedence types.

    • 11:28

  • In this lecture session we learn about recursion in python and also talk about features of recursion in python.

    • 22:15

  • In this lecture session we learn about binary search in python and also talk about features of binary search in python programming.

    • 23:18

  • In this lecture session we learn about binary search in python and also talk about the importance of binary search in python.

    • 35:04

  • In this lecture session we learn about object oriented programming and also talk about features of object oriented programming in brief.

    • 21:52

  • In this lecture session we learn about factors and types of object oriented programming in python programming.

    • 17:41

  • In this lecture session we learn about OOPS and procedural programming and also talk about features of OOPS and procedural programming in OOPS.

    • 06:36

  • In this lecture session we learn about OOPS programs in python and also talk about the importance of OOPS.

    • 27:50

  • In this lecture session we learn about inheritance in python programming and also talk about features of inheritance.

    • 37:24

  • In these lecture sessions we learn about features of object creation in python programming and also talk about object creation in python.

    • 24:10

  • In this lecture session we learn about OOPS terminology and functions and also talk about features of OOPS terminology and functions.

    • 24:41

  • In this lecture session we learn about built in class attributes and garbage collection in python programming.

    • 27:26

  • In this lecture session we learn about inheritance in python and also talk about features of inheritance in python.

    • 19:02

  • In this lecture session we learn about the importance of inheritance in python programming and also talk about functions of inheritance.

    • 29:26

  • In this lecture session we learn about programs in inheritance in python programming and also talk about features of inheritance in python.

    • 31:43

  • In this lecture session we learn about polymorphism in python programming polymorphism and also talk about polymorphism in python.

    • 24:47

  • In this lecture session we learn about features of polymorphism in python and also talk about the importance of polymorphism in python.

    • 14:01

  • In this lecture session we learn about the time module in python and also talk about features time module in python in features.

    • 36:22

  • In this lecture session we learn about the importance of time modules in python time module in python in brief.

    • 44:51

  • In this lecture session we learn about the calendar module in python programming in brief.

    • 32:04

  • In these lecture sessions we learn about calendar methods in python programming and also talk about the importance of calendar methods.

    • 37:03

  • Class 28.1 - Boolean in Python

    • 09:32

  • In this lecture session we learn about python iterators and also talk about features of python iterators in brief.

    • 09:30

  • In this lecture session we learn about python programs and summary in python programming and also talk about python programs.

    • 46:37

  • In this lecture sessions we learn about python programs and also talk about features of python programs and summary.

    • 23:27

Course/Topic 4 - Data Visualization in Python - all lectures

  • In this first video tutorial on Data Visualization in Python course, you will get a brief introduction and overview on what is data visualization, its importance, benefits and the top python libraries for Data Visualization like Matplotlib, Plotly and Seaborn.

    • 25:25

  • In this first part of the video on Matplotlib, you will learn both the theoretical and the practical knowledge on Matplotlib, which is one of the most popular and top python libraries for Data Visualization. You will get a complete introduction to Matplotlib, the installation of Matplotlib with pip, the basic plotting with Matplotlib and the Plotting of two or more lines in the same plot.

    • 30:44

  • In this second part of the Matplotlib video tutorial, you will learn how to add labels and titles like plt.xlabel and plt.ylabel along with understanding how to create lists and insert functions onto it. All this can be seen explained it detail by the instructor by taking examples for it.

    • 21:14

  • In this tutorial, you will learn about 2 important python libraries namely; Numpy and Pandas. Along with the theoretical concepts, you will also get practical implementation on various topics related to these two such as what is Numpy and what is its use, the installation of Numpy along with example, what is pandas and its key features, with the installation of Python Pandas and finally the Data Structure with examples of Pandas.

    • 54:10

  • In this second part of the Numpy and Pandas tutorial, you will learn the complete overview of Pandas like its history, its key features, the installation process of Pandas, Pandas Data Structure and within it the Data Frame and syntax to create Data Frame. All this will be explained in detail by the instructor.

    • 41:10

  • In this third part of the video tutorial on Numpy and Pandas, you will learn about creating Data Frame from Dictionary. Also, you will understand how to read CSV Files with Pandas using practical examples by the Instructor.

    • 30:19

  • In this tutorial, you will learn about the different Data Visualization Tools such as Bar Chart, Histogram and the Pie Chart. You will get a complete understanding of what is these tools, why and how to use these 3 tools, the syntax for creating Bar Chart, Histogram and the Pie Chart and different programs for creating these data visualization tools. In the first part of the video, you will learn about the Bar Chart and in the subsequent videos, you will learn about the Histogram and the Pie Chart.

    • 49:49

  • In this second part of the Data Visualization Tools video, you will learn about the complete overview of Histogram like what is Histogram, how to create Histogram and many others with the help of practical examples by the instructor.

    • 37:01

  • In this third and final part of the Data Visualization Tools video, you will learn about the Pie Chart-what is Pie Chart, how to create the Pie Chart and how to create the syntax for Pie Chart? All these questions will be explained in detail by the instructor by taking practical examples. Further, you will understand the concept of Autoptic parameter in Pie Chart.

    • 47:31

  • In this first part of the video tutorial on more data visualization tools, you will learn about some additional data visualization tools apart from Bar Chart, Histogram and Pie Chart such as Scatter Plot, Area Plot, STACKED Area Plot and the Box Plot. The first part of this tutorial consists of mainly the Scatter Plot, the theoretical concepts associated with it such as what is Scatter Plot, the syntax for creating Scatter Plot and creating Scatter Plot with examples.

    • 35:33

  • In this second part of the video tutorial, you will learn and understand what is Area Plot, creating Area Plot with Function and Syntax and creating Area Plot with examples. All these will be seen explained in detail by the instructor. Further, you will also learn and understand the concept associated with the STACKED Area Plot.

    • 40:32

  • In this final part of the video tutorial, you will learn about the Box Plot; which is also known as Whisker Plot, how to create Box Plot, its syntax and arguments used like Data & Notch, the parameters used in Box Plot such as vert, patch artist and widths. These will be seen explained in detail by the instructor.

    • 36:46

  • In this first video tutorial on Advanced Data Visualization Tools, you will learn about the Waffle Chart – its definition, complete overview, the syntax and programs to create Waffle Chart and the step-by-step procedure to create the Waffle Chart. All these will be seen explained in detail by the instructor.

    • 33:42

  • In this second part of the video tutorial on Advanced Data Visualization Tools, you will learn about the Word Cloud-its definition, the reason why Word Cloud is used, what are the modules needed in generating the Word Cloud in Python, how to install Word Cloud and how to create Word Cloud with the help of some examples.

    • 58:41

  • In this tutorial, you will learn and understand about the concept of Heat Map and how one can create the Heat Map along with the help of the parameter camps. This will be seen explained in detail by the instructor.

    • 37:45

  • In this first part of the video tutorial on Specialized Data Visualization Tools, you will learn about the Bubble Chart; its definition and how to create bubble charts with the help of different examples.

    • 35:55

  • In this video, you will learn about the Contour Plots; which is also sometimes referred to as Level Plots. Along with understanding the whole theoretical concept of Contour Plots, you will also learn how to create Contour Plots with practical examples as will be seen explaining by the instructor in details.

    • 32:04

  • In this third part of the video on Specialized Data Visualization Tools, you will learn about the Quiver Plot and how to create the Quiver Plot by taking different examples. This will be seen explained in complete details by the instructor.

    • 40:49

  • In this video on Specialized Data Visualization Tools, you will learn about 3D plotting in Matplotlib and also the 3D Line Plot used in Data Visualization with the help of different practical examples and how to create it. This will be seen explained in detailed by the instructor throughout the tutorial.

    • 41:41

  • In this tutorial, you will learn about the 3D Scatter Plot and how to create a 3D Scatter Plot. The instructor will be seen explaining this in complete details with the help of different examples.

    • 27:58

  • In this tutorial, you will learn and understand the 3D Contour Plot, what is the function used in creating the 3D Contour Plot and how it can be created; which will be explained in detail by the instructor with the help of examples.

    • 30:18

  • In this last part of the video tutorial on Specialized Data Visualization Tools, you will learn about the 3D Wireframe Plot and the 3D Surface Plot, along with creating the same with the help of different examples, seen explained in detail by the instructor.

    • 43:06

  • In this tutorial, you will learn about Seaborn, which is another very important Python library. Through this video, you will get an introduction to Seaborn, along with some important features of it, functionalities of Seaborn, Installation of Seaborn, the different categories of plot in Seaborn and some basic type of plots one can create using Seaborn like Distribution Plot.

    • 50:52

  • In this second part of the video on Seaborn Library, you will learn and understand some basic plots using Seaborn Library like the Line Plot. Here, the instructor will be seen explaining in detail the Seaborn Line Plot and with a detailed example of how to create Seaborn Line Plot with random data.

    • 24:38

  • This is a continuation video of creating the Line Plot with some more examples using the Seaborn library. Along with this, you will also learn about the Lmplot and the function used for creating the Lmport. This can be seen explained in detailed by the instructor with practical examples.

    • 23:34

  • In this tutorial, you will learn about Data Visualization using Seaborn library. Under this, you will learn the Strip Plot, how to create the strip plot and the program used to create the Strip Plot. This will be shown by the Instructor with detailed examples like Strip plot using inbuilt data-set given in Seaborn and others.

    • 31:37

  • In this video, you will learn about the Swarm Plot; its definition, complete overview and how you can create the Swarm Plot. This can be seen explained in detail by the instructor with examples like visualization of “fmri” dataset using swarm plot().

    • 30:05

  • In this tutorial, you will learn a complete overview on Plotting Bivariate Distribution along with the concepts of Hexbin Plot, Kernel Density Estimation (KDE) and the Reg Plots. You will understand many of the in-depth concepts on these, with detailed explanation by the instructor with examples.

    • 43:18

  • In this tutorial, you will learn about the Pair Plot Function in Visualizing Pairwise Relationship under Seaborn library. You will understand the complete overview of Pair Plot Function, the syntax for using it, the parameters used like hue, palette, kind and diag kind. This will be seen explained in detail by the instructor with the help of examples.

    • 34:31

  • In this tutorial, you will learn about the Box Plot, Violin Plots and the Point Plots – their definitions and how to create them which will be seen explained in detail by the instructor throughout the video.

    • 45:53

Course/Topic 5 - R Programming - all lectures

  • In this lecture session we learn about basic introduction of R programming for beginners and also talk about basic functions of R programming for beginners.

    • 14:34

  • In this tutorial we learn about how we install r programming in our software and also talk about the best way of installing R programming for beginners.

    • 08:50

  • In this lecture session we learn about R's basic data structures including the vector, list, matrix, data frame, and factors. Some of these structures require that all members be of the same data type (e.g. vectors, matrices) while others permit multiple data types (e.g. lists, data frames). Objects may have attributes, such as name, dimension, and class.

    • 07:10

  • In this lecture session we learn about A vector is the basic data structure in R, or we can say vectors are the most basic R data objects.

    • 04:41

  • In this lecture session we learn about R is an ideal tool when it comes to data wrangling. It allows the usage of several preprocessed packages that makes data wrangling a lot more easier. This is one of the main reasons as to why R is preferred in the Data Science community.

    • 19:10

  • In this lecture session we learn about R packages are a collection of R functions, compiled code and sample data. They are stored under a directory called "library" in the R environment. By default, R installs a set of packages during installation. More packages are added later, when they are needed for some specific purpose.

    • 11:25

  • In this tutorial we learn about R is an open-source programming language that is widely used as a statistical software and data analysis tool.

    • 22:33

  • In this lecture session we learn that R can be used as a powerful calculator by entering equations directly at the prompt in the command console. Simply type your arithmetic expression and press ENTER. R will evaluate the expressions and respond with the result.

    • 18:48

  • In this tutorial we learn about Conditional statements are those statements where a hypothesis is followed by a conclusion. It is also known as an " If-then" statement.

    • 28:48

  • In this tutorial we learn about In coding, you ask your computer to check conditions by writing conditional statements. Conditional statements are the way computers can make decisions.

    • 16:15

  • In this lecture session we learn about It is a type of control statement that enables one to easily construct a loop that has to run statements or a set of statements multiple times. For loop is commonly used to iterate over items of a sequence.

    • 25:02

  • In this lecture session we learn about Repeat loop, unlike other loops, doesn't use a condition to exit the loop instead it looks for a break statement that executes if a condition within the loop body results to be true.

    • 15:32

  • In this lecture session we learn that Sum of n natural numbers can be defined as a form of arithmetic progression where the sum of n terms are arranged in a sequence with the first term being.

    • 07:17

  • In this lecture session we learn about The formula to find the sum of n terms in AP is Sn = n/2 (2a+(n−1)d), in which a = first term, n = number of terms, and d = common difference between consecutive terms.

    • 05:52

  • In this tutorial we learn about A switch statement that allows a variable to be tested for equality against a list of values. Each value is called a case, and the variable being switched on is checked for each case.

    • 33:57

  • In this lecture session we learn about Data preprocessing, a component of data preparation, describing any type of processing performed on raw data to prepare it for another data processing procedure.

    • 1:01:55

  • In this tutorial we learn about Data preprocessing is essential before its actual use. Data preprocessing is the concept of changing the raw data into a clean data set. The dataset is preprocessed in order to check missing values, noisy data, and other inconsistencies before executing it to the algorithm.

    • 37:44

  • In this lecture session we learn about Factor in R is a variable used to categorize and store the data, having a limited number of different values. It stores the data as a vector of integer values. Factor in R is also known as a categorical variable that stores both string and integer data values as levels.

    • 37:01

  • In this tutorial we learn about A data frame is a table or a two-dimensional array-like structure in which each column contains values of one variable and each row contains one set of values from each column.

    • 37:47

  • In this tutorial we learn about In R we use merge() function to merge two dataframes in R. This function is present inside the join() function of the dplyr package.

    • 20:37

  • In this lecture session we learn about The R merge function allows merging two data frames by common columns or by row names. This function allows you to perform different database (SQL) joins, like left join, inner join, right join or full join, among others.

    • 25:10

  • In this tutorial we learn about The two data frames must have the same variables, but they do not have to be in the same order.

    • 23:49

  • In this lecture session we learn about merge is a generic function whose principal method is for data frames: the default method coerces its arguments to data frames and calls the "data. frame" method. By default the data frames are merged on the columns with names they both have, but separate specifications of the columns can be given by.

    • 10:08

  • In this lecture session we learn about The functions which are already created or defined in the programming framework are known as a built-in function. R has a rich set of functions that can be used to perform almost every task for the user.

    • 14:32

  • In this lecture session we learn about Melting and Casting are one of the interesting aspects in R programming to change the shape of the data and further, getting the desired shape.

    • 11:35

Course/Topic 6 - Data Visualization in R - all lectures

  • In this introductory tutorial on Data Visualization in R Programming, you will learn about what is data visualization, the type of graph or chart one should select for data visualization, what is the importance and benefits of data visualization and finally what are the applications of data visualization.

    • 28:24

  • In this video, you will learn how to work on the Histogram, which falls under different Chart types used in Data Visualization in R Programming; along with working on the bar chart, box plot and heat map. You will be seeing a detailed explanation by the instructor on the complete workaround of these by taking different examples.

    • 42:00

  • In this video, you will learn what is density plot and how you can create the density plot by taking different examples for it. You will also learn about the different applications being used in the density plot under Data Visualization with R Programming.

    • 17:28

  • In this tutorial, you will learn about Data Visualization with GGPLOT2 Package where inside it you will learn the overview of GGPLOT2, iteratively building plots, univariate distributions and bar plot, annotation with GGPLOT2, axis manipulation and the density plot. You will get a complete understanding of the theoretical concept along with the implementation of each of these.

    • 41:07

  • In this second part of the video tutorial, you will learn about Plotting with GGPLOT2 and building your plots iteratively, along with the importance of the ‘+’ symbol and its use in the GGPLOT2 work process. You will be seeing a detailed explanation from the instructor by taking different examples.

    • 27:40

  • In this video you will learn about the complete theoretical and practical implementation of Univariate Distribution and Bar Plot, which can be seen explained in complete details by the instructor throughout the tutorial.

    • 30:42

  • In this tutorial, you will learn about annotation with ggplot2, along with geom text () and adding labels with geom label () with complete explanation on this by the instructor with the help of different examples.

    • 50:28

  • In this tutorial, you will learn about Axis Manipulation with ggplot2, its complete overview and in-depth concepts along with the different functions used during the process. You will be seeing explaining the topic in complete details by the instructor by taking examples and working in R studio.

    • 34:13

  • In this section, you will learn about Text Mining and Word Cloud, along with the Radar Chart, Waffle Chart, Area Chart and the Correlogram. In this first part of the video, you will learn about the Text Mining and Word Cloud, the different reasons behind using Word Cloud for text data, who is using Word Clouds and the various steps involved in creating word clouds.

    • 31:43

  • In this video, you will learn how to execute data using redline function. Also, you will understand the usage of corpus function and content transformer function. Further, you will understand about the text stemming, Term Document Matrix function and the Max word’s function.

    • 31:49

  • In this tutorial, you will learn about the Radar Chart, the function used in the Radar Chart which is gg Radar (), scales, mapping and the use label. Along with this, you will also learn how to create Radar Chart in R studio. Moreover, you will learn about the Waffle Chart in R and how to create vector data in Waffle Chart with the help of different examples.

    • 34:18

  • In this last part of the session, you will learn about the Area Chart, its in-depth concepts and how to work on it. This will be seen explained in detail by the instructor. Moreover, you will also learn about the Correlogram in R, the correlation matrix, Mt cars and the work around on different visualization methods been used.

    • 39:54

  • This is a project tutorial titled Visualizing COVID-19 where you will see the different scenarios being explained by the tutor on visualizing COVID-19 data and how it can be done through Data Visualization in R process. In this first part, you will understand the complete overview of the project, its description and the different tasks associated with it being done by the ggplot.

    • 34:59

  • In this second part of the project video, you will learn about the “Annotate” process and the number of COVID cases being reported in China with the help of Data Visualization. You will be seeing the task performed on the dataset being provided by the WHO along with understanding the tribble function and how it will help during the entire work process.

    • 37:38

  • In this last part of the session, you will understand the work around of the task being done with the help of plot. You will see a detailed explanation by the instructor seeking help of few examples to explain the complete process of plotting in respect to the COVID-19 project being implemented.

    • 34:50

Course/Topic 7 - Power BI - all lectures

  • Learn how you can leverage Power BI to easily build reports and dashboards with interactive visualizations and see how other organizations have used this solution to drive business results with actionable insights.

    • 20:51

  • In this session, with Power BI Desktop, you can build advanced queries, models, and reports that visualize data. You can also build data models, create reports, and share your work by publishing to the Power BI service.

    • 01:57

  • This is the first part of Basic Dashboard in Power BI. In this video you will learn how to create a basic dashboard with simple data points.

    • 23:35

  • In this Video, we will show you how can you install Power PI desktop in PC.

    • 18:05

  • The third part in a series of Microsoft Power BI tutorials for beginners. This tutorial cover Filter’s pane and the Slicers.

    • 30:14

  • In this Part 4, video shows the time slicer feature of Power BI Desktop. Also running some simple statistics using the matrix visualization.

    • 30:09

  • In this Part 5 session you will learn about how to create a simple R script in Power BI desktop using the grid Extra package for displaying data and the dplyr package for data munging.

    • 21:32

  • In this Microsoft Power BI video, you will learn how to represent the data in a Map using Power BI. For this purpose, a data that contains the columns such as a State, Province, Country, City, ZIP Code/Postal Code, etc. must be present in the database

    • 33:52

  • In this video you can explore, what is Star Schema, why it is important in Power BI, Among the most basic design skills in designing a data warehouse solution is the star schema design.

    • 09:10

  • In this Power BI Tutorial, you will look at how to use Power Query in Power BI Desktop to merge different queries and join kind. This Microsoft Power BI tutorial for beginners is aimed at new Power BI users.

    • 07:49

  • In this video we will go through the basics of data modelling in Power BI, to get you started fast and easy.

    • 01:52

  • In this video, learn how to use relationship’s view, what other views exist in Power BI Desktop and why it's important to use them.

    • 10:39

  • This video explains the importance of cross filter direction in Microsoft Power BI. It discusses how the single or bi-directional filter affects the data in the report.

    • 12:44

  • In this video you will see details about m language and dax language.

    • 16:22

  • In this video you will learn how to create two interactive Power BI dashboards, plus a decomposition tree using the free Power BI tools.

    • 26:35

  • In this video, we will show you how you can use a parameter, within a Power BI report, to dynamically change the data in a report.

    • 15:46

Course/Topic 8 - Power BI (basic to advanced) - all lectures

  • This is an introductory video of Power BI to get you started in this tutorial video, learn how to get started using Microsoft Power BI. Power BI allows you to get insight from your business data.

    • 2:00:46

  • Microsoft Power BI is one of the most popular Data Visualization and Business Intelligence tool. The Power BI tool is the collection of apps, data connectors, and software services which are used to get the data from different data sources, transforms data, and produces useful reports.

    • 1:11:26

  • In Microsoft Power BI services which are based on SaaS and mobile Power BI apps that are available for different platforms. These set of services are used by the business users to consume data and to build Power BI reports.

    • 1:12:22

  • This tutorial helps you to clear all the essential concepts in Power BI and provides enough knowledge on how to use Power BI or how to work on Power BI.

    • 1:03:39

  • The BI term refers to Business Intelligence. It is a data-driven decision support system, which helps you to analyse the data and provide actionable information. It helps the business manager, corporate executives, and other users in making their decisions easily.

    • 1:07:33

  • This Business intelligence refers to the applications, technologies, and practices for the collection, analysis, integration, and presents the business information. The purpose of business intelligence is to support better decision making.

    • 1:15:47

  • Business intelligence is used to improve all parts of a company by improving access to the firm's data and then using that data to increase profitability. Companies that practice BI can translate their collected data into insights their business processors.

    • 1:06:13

  • Power BI is a Data Visualization, and Business Intelligence tool which helps to convert data from different data sources into interactive dashboards and BI reports. It provides interactive visualizations with self-service business intelligence capabilities where end users can create reports and dashboards by themselves, without having to depend on information technology staff or database administrators.

    • 19:07

  • Power BI provides multiple connectors, software, and services. These services based on the SaaS and mobile Power BI apps which are available for different platforms. These set of services are used by business users to consume data and to build BI reports.

    • 1:13:51

  • Power BI dashboard is a single page, also called a canvas that uses visualization to tell the story. It is limited to one page; therefore, a well-designed dashboard contains only the most essential elements of that story.

    • 1:21:57

  • A Power BI report is a multi-perspective view into the dataset, with visualizations which represent different findings and insights from that dataset.

    • 33:47

  • Power BI Desktop and Power BI Services support a large range of data sources. Click on the Get Data button, and it shows you all the available data connections. You can connect to different Flat files, Azure cloud, SQL database, and Web platforms, also such as Google Analytics, Facebook, and Salesforce objects. It includes an ODBC connection to connect to other ODBC data sources.

    • 52:16

  • In this section of the Power BI tutorial, we will learn about each of these Power BI services or components and their roles.

    • 1:15:55

  • In this section, we will briefly walk through a case study of Power BI. This will help to understand the role of Power BI in a real-life scenario.

    • 1:17:30

  • Moving forward in our Power BI tutorials series, let us explore some important features of Power BI thoroughly. Power BI is an efficient business intelligence tool loaded with data visualization and analytics rich features.

    • 06:58

  • This Power BI tutorial we’re going to learn from the basics then we will gradually move upwards, learn about its components and how it works.

    • 1:04:40

  • In this tutorial, we studied Power BI Architecture. Today, we will discuss Power BI Building Blocks. In this Power BI Tutorial, we are going to explore the components of Power BI: Visualizations, Datasets, Reports, Dashboards, and Tiles. So, let’s start the Power BI Building Blocks Tutorial.

    • 1:45:08

  • In this Power BI Tutorial, we will discuss Power BI Query, Power BI Pivot, Power BI View, Power BI Map, Power BI Q&A, Power BI Desktop, Power BI Website, and Power BI Mobile Apps. So, let’s start the Power BI Components Tutorial.

    • 44:44

  • we learn how to download and Install Power BI. First of all, we will see a list of an operating system which supports Power BI. Moreover, we will study, seven simple and quick steps to install power BI on windows.

    • 55:26

  • In this lesson, we are going to discuss the pros and cons of Power BI. As we learned from the tutorial on Features of Power BI, it’s a great tool to use for data analysis and discovering important insights. But, let us go into a little detail and learn about the advantages and disadvantages of Power BI so that you can have some basis to compare it with other tools.

    • 37:17

  • In this Power Bi tutorial, we will study about Power BI data modeling. Moreover, we will see how we use Data Modeling in Power BI, and how to Create Calculated Columns in Data Modeling in Power BI.

    • 54:27

  • In addition, we will talk about how to Create a Calculated table in Power BI Data Modeling and Use information Modeling and Navigation.

    • 40:23

  • In Power BI Tutorial, we talked about Power BI Dashboard. Here, we are going to create Workspace in Power BI or in other words we are creating groups in Power BI Workspace.

    • 40:35

  • Moving forward in our series of Power BI tutorials, the next interesting topic is Power BI Dashboard. Power BI Dashboard is a fundament element in Power BI Desktop.

    • 1:13:29

  • In Power BI tutorial, we studied How to Create Workspace in Power BI. Today, in this instructional exercise, we will figure out how to Share Power BI Dashboard – Outside Organization/Clients. Moreover, we will discuss different ways to share internal & external clients.

    • 1:28:03

  • Despite the fact that Power BI is intended for you to impart a dashboard to clients who are inside a similar association, you can likewise impart dashboards to individuals from different associations.

    • 58:25

  • In this Power BI tutorial, we will learn about how Power BI Create dashboard & report on iPhone, iPad, Android Phone, Android Tablet, Windows 10. Moreover, we will discuss the How power BI view dashboard on land space mode of Windows 10 Devices.

    • 1:00:07

  • Whenever you will search for Power BI Desktop on Google, you will find many websites covering the installation and functions of Power BI in a technical language. But here I am providing you with all the aspects of Power BI in a very simple language.

    • 54:52

  • In this Power BI tutorial, we will learn about Interface with information in Power BI work area. Moreover, we will learn how to connect to data in Power BI Desktop.

    • 50:23

  • In our tutorial, we discussed Analytics Pane in Power BI. Today, in this Q & A in Power BI Desktop Tutorial, we will learn how to add a missing relationship and rename tables and columns. Moreover, we will study how to fix incorrect data types and choose the data category for each date and geography column. At last, we will cover to normalize your model.

    • 58:34

  • In this tutorial, we will study Power BI Measure. Today, we are going to learn the Power BI Archived Workspace. Moreover, we will study the Confinements and Moving Content in your Archived Workspace in Power BI. At last, we will cover the Power BI Archived Workspace in Office 365.

    • 46:31

  • In this video, we talked about the Power BI Archived Workspace. In this Power BI Data Source Tutorial, we are going to learn Data Sources for Power BI Services. Moreover, we are going to discuss how data originates from an alternate source and some subtle elements. Along with this, we will cover the types of data sources for Power BI.

    • 42:23

  • In this Power BI tutorial, we will study Power BI Data Source. Today in this Power BI Admin tutorial, we will learn about the various roles of Power BI administration: Purchasing, REST API, and Security.

    • 1:17:24

  • Continuing with our Power BI tutorial series, now, we will learn about Power BI Report Server. As we know, Power BI as a technology is a collection of several other technologies and services. Power BI Report Server is one such crucial technology. Here, we will learn about its different aspects.

    • 52:22

  • In this session we are going to explore the working of a table in Power BI. In addition, we will discuss when to use a Power BI table with its prerequisites. Along with this we will study how to Create a table & Format the table, and adjust the column width of a table in Power BI.

    • 40:57

Course/Topic 9 - Tableau - all lectures

  • In this video lecture we learn basic about Tableau. Tableau is a business intelligent tool for visually analysing the data.

    • 10:01

  • In this video we talk about Tableau Desktop Basics and also cover all the Basic topics of Tableau Desktop.

    • 02:32

  • In this video we learn how to install Tableau business intelligent tool into your desktop and process of Tableau Desktop Installation.

    • 06:28

  • In this video we about Tableau Desktop Workspace Navigation and cover all the importance of Tableau Desktop Workspace Navigation.

    • 10:40

  • In this session we talk about Tableau Design Flow and also cover all the different types of Tableau Design Flows.

    • 07:08

  • In this video we learn about Connections to Multiple Data Sources and cover all techniques of data sourcing.

    • 18:04

  • In this video we talk about Hands-on - Tableau Data Connection and also cover different between live and exact Tableau Data Connection.

    • 21:51

  • In this session we learn basic about Tableau Filters and different types of filters we can use in Tableau business tool.

    • 31:46

  • Data can be organized and simplifies by using various techniques in Tableau. In this session we also cover types of filters and condition of filters in Tableau.

    • 16:06

  • In this session we learn about Tableau Operators. Types of Tableau Operators and how to use these Tableau Operators.

    • 18:30

  • In this video we talk about Bins - Groups - Sets – Parameters and also cover all the parameters we use in Tableau.

    • 15:00

  • In this session we learn about Hands on - Tableau Sets and cover all different sets in Hands on - Tableau Sets..

    • 13:35

  • In this session we talk about Basic Tableau Charts and learn about different types of charts.

    • 23:26

  • In this video we talk about Hands on - Basic Tableau Charts how to make pie chart and importance of charts in Tableau business tool.

    • 21:24

  • In this lecture we learn the Tableau Advanced Topics like Advance graphs, LODS and its usage and extensions etc.

    • 03:03

  • In this video we talk about Tableau Extensions and cover all different types of extensions in a single video.

    • 21:20

  • In this Lecture section we talk and overview the Tableau Dashboards and explore the Dashboards of Tableau.

    • 26:30

  • In this lecture session we talk about the Tableau Story. In Tableau story is a sequence of visualization that work together to convey the information.

    • 20:27

  • In this video we talk about Tableau LODs extension and importance of LODs extension in Tableau business tool.

    • 18:55

  • In this lecture session we talk about Tableau Actions and also cover all Actions filters.

    • 26:53

Course/Topic 10 - Tableau (comprehensive) - all lectures

  • In this session you will learn about the Business intelligence (BI) which combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions

    • 17:31

  • In this session we will introduce you about Tableau which is a widely used business intelligence (BI) and analytics software trusted by companies like Amazon, Experian, and Unilever to explore, visualize, and securely share data in the form of Workbooks and Dashboards. With its user-friendly drag-and-drop functionality it can be used by everyone to quickly clean, analyze, and visualize your team’s data.

    • 33:45

  • This session is all about the history of Tableau which was founded by Pat Hanrahan, Christian Chabot, and Chris Stolte from Stanford University in 2003. The main idea behind its creation is to make the database industry interactive and comprehensive.

    • 21:38

  • In this tutorial, we will discuss the Tableau interface and understand its functioning in detail. Followed by the general understanding of Tableau’s working. Along with this, we will learn the Components of Tableau Server.

    • 34:10

  • In this session, you will get to know how to use Tableau Prep Builder to clean and prepare your data, start a new flow by connecting to your data, just like in Tableau Desktop. You can also open an existing flow and pick up where you left off.

    • 43:54

  • In this video, once you have chosen the best Tableau product for you, it is time to start finding insights in your data! Much like Tableau’s suite of products, data connections come in many shapes and sizes. As of this writing, Tableau Desktop: Personal has four different types of data connections, and Tableau Desktop.

    • 33:13

  • This session teaches you about the Data blending which is a method for combining data from multiple sources. Data blending brings in additional information from a secondary data source and displays it with data from the primary data source directly in the view.

    • 30:50

  • If you are connected to a data source that has been modified, you can immediately update Tableau Desktop with the changes by selecting a data source on the Data menu and then selecting Refresh.

    • 41:22

  • In this Tableau tutorial, we are going to study about what is sorting in Tableau. We will also discuss how to use Quick Sort in Tableau. At last, we will see why is my king broken and combined filed. Tableau sort is the process of arranging or ordering the data in Ascending Order or Descending Order.

    • 19:38

  • In this video, we will show you How to perform sorting in Tableau reports with example. For this Tableau sort demo, we are going to use the report we created in our previous article.

    • 13:43

  • In this tutorial, we will show you How to perform grouping in Tableau reports with example. For this Tableau Grouping demo, we are going to use the report we created in our previous article. Tableau Grouping is the process of merging or combining two or more values for further analysis.

    • 12:18

  • In this video, we will show you How to perform grouping in Tableau reports with example? For this Tableau Grouping demo, we are going to use the report we created in our previous video.

    • 24:55

  • In this video, we will show you how to create Tableau Set, Constant Sets, and Computed Sets. First, Drag and Drop the State Name from Dimension Region to Rows Shelf and Profit from Measures region to Columns Shelf.

    • 26:50

  • In addition to a Set Action, you can also allow users to change the membership of a set by using a filter-like interface known as a Set Control, which makes it easy for you to designate inputs into calculations that drive interactive analysis. For details, see Show a set control in the video.

    • 38:06

  • In this session you begin filtering data in Tableau, it's important to understand the order in which Tableau executes filters in your workbook. Filtering is an essential part of analyzing data. This article describes the many ways you can filter data from your view. It also describes how you can display interactive filters in the view, and format filters in the view.

    • 26:07

  • In this video you will get to know about filtering which is an essential part of analyzing data. This article describes the many ways you can filter data from your view. It also describes how you can display interactive filters in the view, and format filters in the view.

    • 20:49

  • In this tutorial, we will learn about another interesting and useful feature of Tableau that is Tableau parameters. Here, we will try and gain a good understanding of the parameters in Tableau and their use in Tableau. We will start by discussing the definition of parameters followed by learning how to create parameters and use them in Tableau.

    • 31:36

  • In this session you will understand how to use parameter actions to let your audience change a parameter value through direct interaction with a viz, such as clicking or selecting a mark. You can use parameter actions with reference lines, calculations, filters, and SQL queries, and to customize how you display data in your visualizations.

    • 24:43

  • In this Tableau tutorial, we will study What is Tableau Reference Lines, functions of Reference lines in Tableau and the steps involved in creating / Adding reference lines to the Tableau Bar Chart. At last, we will how to create reference lines in Tableau with example. So, let us start Tableau Reference Lines.

    • 20:42

  • In the tutorial you will get to know how to show trend lines in a visualization to highlight trends in your data. You can publish a view that contains trend lines, and you add trend lines to a view as you edit it on the web. When you add trend lines to a view, you can specify how you want them to look and behave.

    • 25:39

  • In this Tableau tutorial, you will learn about the story which is a sequence of visualizations that work together to convey information. You can create stories to tell a data narrative, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case.

    • 23:15

  • In this session you will understand how to Use stories to make your case more compelling by showing how facts are connected, and how decisions relate to outcomes. You can then publish your story to the web or present it to an audience. Each story point can be based on a different view or dashboard, or the entire story can be based on the same visualization seen at different stages, with different filters and annotations.

    • 41:34

  • In this video, we will show you, How to Format Tableau Dashboard Layout with an example. For this, we are going to use the below-shown dashboard. Once you created your dashboard (added required Sheets), you can use the layout tab to format those Sheets or Items as per your requirements.

    • 23:52

  • Tableau Layout Containers control the spacing between dashboard components. They allow you to format common elements and move multiple dashboard objects at the same time. 

    • 36:38

  • In our last Tableau tutorial, we discuss How to Format Tableau Dashboard Layout. Here, in this tutorial, we are going to learn about How to Tableau Interactive Dashboard with Data Granularity, Interactivity, and Intuitiveness in Tableau. In other word or in general words we can call this playing with maps in a tableau. so, let us start with How to Create Tableau Interactive Dashboard.

    • 29:40

  • This tutorial walks you through some of the most common tasks you might perform when creating maps in Tableau. You’ll learn how to connect to and join geographic data; format that data in Tableau; create location hierarchies; build and present a basic map view; and apply key mapping features along the way. If you're new to building maps in Tableau, this a great place to start.

    • 07:55

  • This tutorial describes how to create and use calculated fields in Tableau using an example. You'll learn Tableau calculation concepts, as well as how to create and edit a calculated field. You will also learn how to work with the calculation editor, and use a calculated field in the view. If you're new to Tableau calculations or to creating calculated fields in Tableau, this is a good place to start.

    • 21:08

  • You can build several different types of maps for your geographic analysis in Tableau. If you're new to maps, or simply want to take advantage of the built-in mapping capabilities that Tableau provides, you can create a simple point or filled (polygon) map.

    • 13:07

  • You can always customize a table calculation by editing it in the Table Calculations dialog box, but there are other, more specialized ways to customize a table calculation.

    • 14:15

  • This video introduces the basics of understanding calculations in Tableau. In this topic, you'll learn why and when to use calculations.

    • 14:17

  • This session explains the types of LOD expressions you can use in Tableau, as well as when to use them, and how to format them. It also uses an example to demonstrate how to create a simple LOD expression. Level of Detail expressions (also known as LOD expressions) allow you to compute values at the data source level and the visualization level. However, LOD expressions give you even more control on the level of granularity you want to compute.

    • 27:50

  • To edit a table calculation Right-click the measure in the view with the table calculation applied to it and select Edit Table Calculation. In the Table Calculation dialog box that appears, make your changes.

    • 18:31

  • Tableau can create interactive visualizations customized for the target audience. In this tutorial, you will learn about the measures, chart types and its features.

    • 15:18

  • When you save a level of detail expression, Tableau adds it to either the Dimensions or the Measures area in the Data pane. FIXED level of detail expressions can result in measures or dimensions, depending on the underlying field in the aggregate expression.

    • 37:12

  • In this Tableau tutorial, we are going to learn about using a Histogram in Tableau. Here, we will find answers to questions like what is a histogram, and how do we create it in our Tableau software.

    • 16:11

  • In this tutorial, 'Sample-Superstore.csv' is used for the demonstration. You can connect to the data source and follow the steps given in the tutorial. Tableau can create interactive visualizations customized for the target audience. In this tutorial, you will learn about the measures, chart types and its features.

    • 25:01

  • In this Tableau Tutorial, we are going to learn about an interesting chart that is a bubble chart or packed bubble chart. Here, we will learn how to create a bubble chart in Tableau in a stepwise manner. You can create your first Tableau bubble chart with us on your own device. All you need, as of now is a sample data set and Tableau software in your device.

    • 09:54

  • A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.

    • 11:51

  • Tableau Bubble Chart is used to display the data in circles. We can define each bubble using any of our Dimension members and size by Measure value.

    • 09:54

  • In this tutorial we will learn about Tree maps which are the relatively simple data visualization that can provide insight in a visually attractive format. Use packed bubble charts to display data in a cluster of circles. Dimensions define the individual bubbles, and measures define the size and color of the individual circles.

    • 10:42

  • In this Video we will get to know about the best practices which are key to developing informative visualizations that drive your audience to act. A dashboard is successful when people can easily use it to derive answers. Even a beautiful dashboard with an interesting data source could be rendered useless if your audience can’t use it to discover insights.

    • 48:07

Course/Topic 11 - SAS Business Intelligence - all lectures

  • This tutorial teaches you the integrated platform for delivering enterprise intelligence. This platform, which we call the SAS Enterprise Intelligence Platform, optimally integrates individual technology components within your existing IT infrastructure into a single, unified system.

    • 1:26:02

  • This session teaches the change management feature enables a team of SAS Data Integration Studio users to work simultaneously with a set of related metadata and avoid overwriting each other's changes. With change management, most users are restricted from adding or updating the metadata in a change-managed folder in the Folders tree.

    • 1:32:54

  • This teaches you the Data marts which are small slices of data warehouse. This module is a collection of tips on how to run your data mart implementation project Planning a Data Warehouse, Exercises

    • 1:26:33

  • This Help you to Learn how to build a data mart during SAS BI training, starting from reviewing a case study. Review of the Case Study, Define the Source Data, what are the Target Tables in SAS BI, Load the Target Tables, Exercises

    • 1:21:55

  • In this session, you will learn the On-Line Analytical Processing (or OLAP) has long been part of the data storage and exploitation strategy for SAS professional. Take an overview on OLAP in this module of SAS BI Training. What Is OLAP, Building an OLAP Cube in SAS BI, Solutions to Exercises

    • 1:11:53

  • This tutorial is designed to give you a good idea about SCD, its dimensions, load transformation and Lookup transformation. Defining Slowly Changing Dimensions in SAS BI How to use SAS BI SCD Type 2 Loader Transformation Using the Fact Table Lookup Transformation

    • 55:41

  • This session teaches you how to schedule data integration studio jobs during SAS BI training. Scheduling SAS Data Integration Studio Jobs

    • 1:11:38

  • In this session you will understand about the online analytical processing concepts, building an OLAP cube with SAS OLAP Cube Studio, building an information map from a SAS OLAP cube

    • 1:21:09

  • This video teaches you about the introduction to SAS Visual BI and exploring the SAS integration with JMP

    • 1:17:56

  • This tutorial helps you to Reviewing the platform for SAS Business Analytics and reviewing the course environment

    • 54:13

  • This video teaches you about the SAS Stored Process concepts, creating a stored process from a SAS Enterprise Guide project creating a stored process from a SAS program, creating stored process parameters, creating a stored process to provide a dynamic data source

    • 57:18

Course/Topic 12 - Talend - all lectures

  • Lecture 1 - Talend Introduction

    • 15:06

  • Lecture 2 - Architecture and Installation - part 1

    • 49:38

  • Lecture 3 - Architecture and Installation - part 2

    • 54:24

  • Lecture 4 - Architecture and Installation - part 3

    • 47:31

  • Lecture 5 - File - Java - Filter Components

    • 53:39

  • Lecture 6 - tAggregateRow - tReplicate - tRunJob Components - part 1

    • 53:40

  • Lecture 7 - tAggregateRow - tReplicate - tRunJob Components - part 2

    • 06:17

  • Lecture 8 - Join Components - part 1

    • 38:00

  • Lecture 9 - Join Components - part 2

    • 19:34

  • Lecture 10 - Sort Components

    • 29:26

  • Lecture 11 - Looping Components

    • 24:19

  • Lecture 12 - Context - part 1

    • 37:48

  • Lecture 13 - Context - part 2

    • 33:37

  • Lecture 14 - Slowly Changing Dimensions (SCD)

    • 44:55

  • Lecture 15 - tMap Components - part 1

    • 31:15

  • Lecture 16 - tMap Components - part 2

    • 37:47

  • Lecture 17 - tMap Components - part 3

    • 33:42

  • Lecture 18 - tMap Components - part 4

    • 13:43

  • Lecture 19 - Talend Error Handling

    • 56:03

  • Lecture 20 - Audit Control Jobs

    • 47:55

  • Lecture 21 - How to use tJAVA components with scenario

    • 54:12

  • Lecture 22 - Talend Big Data Hadoop Introduction and Installation

    • 31:57

  • Lecture 23 - Talend HIVE Components - part 1

    • 47:34

  • Lecture 24 - Talend HIVE Components - part 2

    • 24:42

  • Lecture 25 - Talend HDFS Components

    • 57:50

  • Lecture 26 - Talend TAC

    • 30:31

Course/Topic 13 - SQL Programming with MySQL Database - all lectures

  • In this video get an in-depth introduction to the terminology, concepts, and skills you need to understand database objects, administration, security, and management tools. Plus, explore T-SQL scripts, database queries, and data types

    • 30:09

  • In this video learn basic of SQL Programming and overview the SQL basic commands and how we use these commands in SQL Programming. This SQL tutorial will teach you basics on how to use SQL in MySQL, SQL Server, MS Access, Oracle, Sybase, Informix, Postgres, and other database systems.

    • 42:45

  • In this video we talk about DDL (DATA DEFINATION LANGUAGE) and also cover all the basic techniques of DDL.In this video we will learn about the SQL commands – DDL, DML, DCL; SQL Constraints – Keys, Not Null, Check , Default, and also MYSQL Hands-on and basic Querying

    • 33:59

  • In this video session we learn SQL commands and how to use these commands like select command, insert command, delete command etc. In this video we will learn about hands-on experience on the terminal, creating database, Tables and manipulating data.

    • 38:49

  • In this video we learn about SQL Basic and Aggregate Functions and also cover different functions of SQL. This tutorial teaches us about clauses and the update command. We will also cover making records, updating and modifying rows.

    • 37:02

  • In this session we talk about SQL Regular Expression and we also cover all techniques of SQL Regular Expression.This tutorial teaches us about clauses and the update command. We will also cover making records, updating and modifying rows and EML commands.

    • 36:07

  • In this video we learn about SQL Comparison Clauses and how we use Comparison Clauses in SQL. This tutorial covers Comparison Operators by relating values by a mathematical symbol which is used to compare two values. Learn about comparison operators result - TRUE, FALSE, or UNKNOWN

    • 28:30

  • In this session we learn about SQL String and also cover all types of string in SQL and how we can use SQL Strings. In this video we will learn about the basic string functions such as concat_ws, file format, and insert function, L-case, u case, and lower case. We will also learn about basic functions such as upper functions.

    • 30:31

  • In this session we cover advance level string function and also cover all different commands we use in SQL String Function. This video is a sequel for string functions tutorial. In this tutorial we will learn few most useful string functions such as spaces and null issue as well, L-Pad command.

    • 38:20

  • In this SQL String function part 3 we learn select Repeat function and Select Replace function and also cover different between Select Repeat function and Select Replace function. This tutorial is another sequel to string functions, however, these functions are used less and not used that frequently. We will further learn here about the repeat function, absolute function, ceiling, and floor and down functions.

    • 23:20

  • In this session we learn about SQL Numeric Functions and how we use Numeric functions in SQL. In this video, we will be covering numerical functions. Learn about the basic date functions and also about truncate functions.

    • 36:50

  • In this video session we learn about SQL Numeric Function and also cover the basic functionality of SQL Numeric Function. SQL Data Functions. In this video we will learn about few more Date functions. We will further look into the day function option as well. This tutorial covers basic querying over a single table.

    • 46:38

  • : In this video we talk about SQL Joins Introduction and Demonstration and basic join’s function and how to make table using joins. In this tutorial learn about joints in SQL. This tutorial teaches us how to connect two different tables with joints. We will also cover the topic of querying two or more tables and about subquery .

    • 36:52

  • In this lecture last session we talk about MySQL Workbench and procedures and Views and MySQL Workbench functionality. In this tutorial learn about SQL in automating things. This tutorial covers stroll procedure, functions and views which are helpful for automation purposes in SQL.

    • 21:22

Course/Topic 14 - Microsoft Excel - all lectures

  • Lecture 1 - Introduction to Microsoft Excel

    • 19:48

  • Lecture 2 - Key in Data

    • 12:46

  • Lecture 3 - Font and Alignment

    • 13:52

  • Lecture 4 - Cut Paste and Format Painter

    • 07:20

  • Lecture 5 - Control plus Keys

    • 23:40

  • Lecture 6 - Home Commands and Clipboard

    • 20:09

  • Lecture 7 - File Tab

    • 12:49

  • Lecture 8 - Sorting and Filtering

    • 26:09

  • Lecture 9.1 - Basic Formulas

    • 23:00

  • Lecture 9.2 - Text Formulas

    • 32:49

  • Lecture 10.1 - VLookup - part 1

    • 26:39

  • Lecture 10.2 - VLookup - part 2

    • 06:20

  • Lecture 10.3 - HLookup

    • 14:22

  • Lecture 10.4 - This is a bonus session on Vlookup from a different tutor

    • 10:27

  • Lecture 10.5 - This is a bonus session on Vlookup from a different tutor

    • 05:02

  • Lecture 11.1 - Pivot Tables - part 1

    • 15:16

  • Lecture 11.2 - Pivot Tables - part 2

    • 07:14

  • Lecture 11.3 - Pivot Tables - part 3

    • 23:38

  • Lecture 11.4 - Pivot Tables - part 4

    • 11:47

  • Lecture 12.1 - Charts - part 1

    • 09:05

  • Lecture 12.2 - Charts - part 2

    • 21:01

  • Lecture 12.3 - Column Charts

    • 30:28

  • Lecture 12.4 - Bar Charts

    • 09:07

  • Lecture 12.5 - Line Charts

    • 09:57

Course/Topic 15 - Google Sheets course - all lectures

  • Lesson 1 - Introduction to Google Sheets

    • 02:31

  • Lesson 2 - Menu Options - File

    • 08:40

  • Lesson 3 - Menu Options - Edit

    • 03:30

  • Lesson 4 - Menu Options - View

    • 04:49

  • Lesson 5 - Menu Options - Insert

    • 04:59

  • Lesson 6 - Menu Options - Format

    • 10:21

  • Lesson 7 - Menu Options - Data and more

    • 18:17

  • Lesson 8 - Entering Data and Editing

    • 07:12

  • Lesson 9 - Functions - Numeric Function

    • 15:24

  • Lesson 10 - Functions - Text Function

    • 30:38

  • Lesson 11 - Functions - Date Functions

    • 06:21

  • Lesson 12 - Charts and Conditional Formatting

    • 22:12

  • Lesson 13 - Pivot Tables

    • 23:21

  • Lesson 14 - Saving - Sharing

    • 06:22

Course/Topic 16 - Project Management Fundamentals - all lectures

  • In this first video tutorial on Project Management, you will learn an Introduction to Project Management, its history, benefits, an illustration to Gantt Chart, a view on some of the International standards of practicing Project Management, an overview of what exactly is a project, its relationship with General Project Management practices, Triple Constraints Theory and the role of a Project Manager and its characteristics in Project Management.

    • 39:36

  • In this second session of Project Management, you will understand what is Process Oriented Project Management, Project Processes and its categories, what is Project Management and Product Oriented processes and an overview of different process groups and its knowledge areas.

    • 21:23

  • In this lecture, you will learn what is a process in Project Management and its different stages in a Project Life cycle, how a process is linked to different process groups. Also, you will learn about the different Knowledge Areas related to a Process in Project Management.

    • 28:19

  • In this video, you will learn about the Project Planning Process and Group Processes and the different processes involved in managing the Scope and Scheduled Constraints.

    • 26:25

  • In this last session on Project Management Fundamentals, you will learn about the different constraints involved like Cost, Quality, Resources, Risks, etc. in a Process Group and how it helps in managing the entire project in Project Management.

    • 20:36

Course/Topic 17 - Microsoft Project (basic to advanced) - all lectures

  • Lecture 1 - Overview of Microsoft Project

    • 07:47

  • Lecture 2 - The Stage

    • 24:17

  • Lecture 3 - The Back Stage

    • 17:29

  • Lecture 4 - Views and Tables in MSP

    • 24:03

  • Lecture 5 - Project Initiation - part 1

    • 27:44

  • Lecture 6 - Project Initiation - part 2

    • 07:16

  • Lecture 7 - Tasks and Milestones

    • 24:00

  • Lecture 8 - Linking Tasks

    • 28:24

  • Lecture 9 - More on Linking Tasks

    • 29:41

  • Lecture 10 - Creating Resources

    • 29:04

  • Lecture 11 - Creating Resources - advanced

    • 23:25

  • Lecture 12 - Assigning Resources

    • 27:58

  • Lecture 13 - Applying Cost Tables

    • 11:42

  • Lecture 14 - Units Work Duration

    • 34:39

  • Lecture 15 - Handy Features - revised

    • 09:36

  • Lecture 16 - Critical Path Identification

    • 15:58

  • Lecture 17 - Resource Leveling

    • 21:15

  • Lecture 18 - Baselining

    • 16:02

  • Lecture 19 - Updating Project - part 1

    • 25:48

  • Lecture 20 - Updating Project - part 2

    • 17:44

  • Lecture 21 - Updating Project - part 3

    • 23:29

  • Lecture 22 - Monitoring

    • 28:24

  • Lecture 23 - Controlling - part 1

    • 22:52

  • Lecture 24 - Controlling - part 2

    • 19:54

  • Lecture 25 - Reports Pack

    • 32:56

  • Lecture 26 - Support EVM

    • 11:58

Course/Topic 18 - Leadership and Management - all lectures

  • In this lecture session we learn about honesty and integrity in leadership and management and also talk about some basic terms of leadership and management.

    • 23:44

  • In this lecture session we learn about how confidence is a must in leadership and management and also talk about the importance of confidence in leadership and management.

    • 34:07

  • In this tutorial we learn about A soft skill is a personal attribute that supports situational awareness and enhances an individual's ability to get a job done. The term soft skills is often used as a synonym for people skills or emotional intelligence.

    • 20:31

  • In this lecture session we learn about Soft skills, also called people skills, are the mix of social and interpersonal skills, character traits, and professional attitudes that all jobs require. Teamwork, patience, time management, communication, are just a few examples.

    • 22:58

  • In this lecture session we learn that Communication in teams is more than just efficient work. It allows everyone on the team to be educated on any topic that may affect their work. Moreover, it develops trust, builds camaraderie among the team members, boosts morale, and helps employees stay engaged in the workplace.

    • 26:44

  • In this lecture session we learn about Effective communication can help to foster a good working relationship between you and your staff, which can in turn improve morale and efficiency.

    • 29:21

  • In this lecture session we learn about what commitment Concentration – leadership commitment involves making a personal decision to support the change no matter what. It is incongruous to ask for change in others while failing to exhibit the same level of commitment. Concentration requires maintaining focus throughout the change not just at the beginning.

    • 15:12

  • In this lecture session we learn about Market leadership is the position of a company with the largest market share or highest profitability margin in a given market for goods and services. Market share may be measured by either the volume of goods sold or the value of those goods.

    • 36:11

  • In this lecture session we learn that Motivational leadership is defined by positivity and vision. Motivational leaders make decisions, set clear goals and provide their teams with the empowerment and tools to achieve success. Motivational leaders evoke and see the best in their employees, inspiring them to work toward a common goal.

    • 30:53

  • In this lecture session we learn about A primary task of leadership is to direct attention. To do so, leaders must learn to focus their own attention. When we speak about being focused, we commonly mean thinking about one thing while filtering out distractions.

    • 28:19

  • In this tutorial we learn about Marketing analytics helps collect and strengthen data from across all marketing channels. This information is key to improving marketing efforts and driving them forward to achieve business goals.

    • 37:05

  • In this lecture session we learn about Marketing automation is the integration of data and processes from other sales and marketing channels into an organized central platform. A comprehensive marketing automation hub complements and organizes the customer journey. It integrates all of a business's channels and outreach within the customer database.

    • 32:03

  • In this tutorial we learn about Growth hacking (also known as 'growth marketing') is the use of resource-light and cost-effective digital marketing tactics to help grow and retain an active user base, sell products and gain exposure.

    • 31:59

  • In this tutorial we learn about Growth Hacking is a new field focusing solely on growth, based on a data-driven, experiment-based process. A growth hacker explores new growth opportunities systematically in any part of the customer journey, from awareness through marketing to brand ambassadors by optimizing the product.

    • 27:50

  • In this lecture session we learn about Product marketing is the process of bringing a product to market. This includes deciding the product's positioning and messaging, launching the product, and ensuring salespeople and customers understand it. Product marketing aims to drive the demand and usage of the product.

    • 30:51

  • In this lecture session we learn about the marketing, sales, product, and customer success teams are no longer siloed. They are interwoven in a cohesive experience with the product at the center, and the customer at the center of the product.

    • 27:38

  • In this tutorial we learn about how Product marketers know the message and story to convey, who to convey it to, and at what time it needs conveying- but marketing is responsible for turning that knowledge into blog posts, ad copy, and press releases.

    • 18:16

  • In this lecture session we learn about PR involves communicating with your market to raise awareness of your business, build and manage your business's reputation and cultivate relationships with consumers. While marketing focuses on promoting actual products and services, public relations focuses on promoting awareness, attitudes and behavior change.

    • 34:17

  • In this lecture session we learn about building relationships with the public in order to create a positive public image for a company or organization. It also has different disciplines, such as corporate communications, internal communications, marketing communications, crisis communications.

    • 37:40

  • In this lecture session we learn about Public relations helps build an online presence across multiple platforms – social media, earned media, paid media and more. Public relations is important because it involves storytelling. Advertising and marketing can only go so far, and can become bothersome at times, turning consumers away from the product.

    • 33:06

  • In this lecture session we learn about Both advertising and PR help build brands and communicate with target audiences. The most basic difference between them is that advertising space is paid while public relations results are earned through providing the media with information in the form of press releases and pitches

    • 17:49
Course Objectives Back to Top

The Career Path - Data Consultant course is designed to equip participants with the essential skills and knowledge necessary to excel in the role of a Data Consultant. This intensive course covers a wide range of topics crucial for data analysis, business intelligence, cloud computing, programming, data visualization, and project management. Upon completion of this course, participants will possess a diverse and specialized skill as a Data Consultant in various industries and organizational contexts. By the end of the course, participants will be able to Master Business Intelligence and Data Analytics, Understand Cloud Computing Basics, Data Visualization in Python and Master Power BI (Basic to Advanced).

 

Key Course Objectives

1. Principles and practices of business intelligence (BI)

2. Data analysis and visualization techniques

3. Introduction to cloud computing models (IaaS, PaaS, SaaS)

4. Cloud deployment models (public, private, hybrid)

 

Course Syllabus Back to Top

1.Business Finance and Financial Modeling

a)Principles of finance in business

b)Financial modeling techniques

c)Budgeting and forecasting

 

2.Cost and Management Accounting

a)Cost accounting fundamentals

b)Management accounting techniques

c)Cost analysis and decision-making

 

3.Leadership and Management

 a)Leadership styles and principles

 b)Team management and motivation

 c)Strategic management concepts

 

4.Product Management

a)Product lifecycle management

b)Market research and analysis

c)Product development strategies

 

5.Project Management Fundamentals

a)Project planning and scheduling

b)Risk management in projects

c)Agile and Waterfall methodologies

 

6.SAP BPC (Business Planning and Consolidation)

a)Overview of SAP BPC functionalities

b)Financial planning and consolidation processes

c)Reporting and analysis capabilities

 

7.Business Intelligence and Data Analytics

a)Introduction to business intelligence concepts

b)Data visualization techniques

c)Data-driven decision-making

 

8.Microsoft Excel

a)Advanced Excel functions and formulas

b)Data analysis using Excel

c)Excel for financial modeling

 

9.Google Sheets

a)Spreadsheet basics and advanced features

b)Collaborative data analysis using Google Sheets

c)Integration with other Google Workspace tools

 

10.SQL Programming

 a)SQL basics and querying techniques

 b)Database management and manipulation

 c)Data extraction for reporting and analysis

 

11.Tableau

 a)Introduction to Tableau and data visualization

 b)Creating interactive dashboards

 c)Advanced analytics with Tableau

 

12.Power BI

 a)Power BI fundamentals and architecture

 b)Data modeling and transformation

 c)Creating and sharing Power BI reports and dashboards

 

13.SAP BusinessObjects (BO) Business Intelligence

 a)Overview of SAP BO BI tools

 b)Reporting and dashboard creation

 c)Integration with SAP and other data sources

 

Certification Back to Top

A career as a Data Consultant involves working with data to provide insights, support decision-making, and solve complex business problems. Data consultants require a strong foundation in data analysis, management, and visualization, along with skills in data engineering and strategic thinking. Here are some of the top certifications for a Data Consultant, along with the benefits of each:

 

Top Certifications for Data Consultants

1.Microsoft Certified: Data Analyst Associate (Power BI) Overview: This certification, offered by Microsoft, focuses on using Power BI to prepare, model, visualize, and analyze data.

Benefits: Data Visualization Expertise: Demonstrates your ability to create interactive and insightful data visualizations using Power BI. Industry Demand: Power BI is widely used in businesses for data analysis and reporting, enhancing your employability. Skill Validation: Validates your proficiency in data analysis and business intelligence tools.

2.Certified Analytics Professional (CAP): Offered by the INFORMS organization, CAP certification is designed for professionals who want to validate their expertise in analytics and data-driven decision-making.

Benefits: Comprehensive Skills: Covers a broad range of analytics skills, including problem definition, data analysis, and model building. Professional Recognition: Enhances your credibility as an analytics professional and validates your ability to apply analytics in real-world scenarios. Career Growth: Opens up opportunities in various industries where advanced analytics are essential.

3.Google Data Analytics Professional Certificate: Offered by Google on Coursera, this certification covers fundamental data analytics skills, including data cleaning, analysis, and visualization using tools like Excel and SQL.

Benefits: Fundamental Skills: Provides a strong foundation in data analytics techniques and tools. Practical Experience: Includes hands-on projects that help you build real-world data analysis skills. Career Entry: Ideal for individuals looking to start a career in data analytics and consulting.

4.AWS Certified Data Analytics: Specialty Overview: Offered by Amazon Web Services (AWS), this certification focuses on data analytics and Big Data solutions using AWS services.

Benefits: Cloud Analytics Skills: Demonstrates your ability to design and implement data analytics solutions using AWS cloud services. Industry-Relevant: AWS is a leading cloud platform used by many organizations, enhancing your marketability. Advanced Knowledge: Validates your expertise in managing and analyzing large datasets in a cloud environment.

5.Certified Data Management Professional (CDMP): Offered by the Data Management Association International (DAMA), CDMP certification focuses on data management best practices and principles.

Benefits: Data Management Expertise: Validates your skills in data governance, data quality, and data architecture. Industry Standard: Recognized globally as a standard for data management professionals. Career Advancement: Opens opportunities in data management, governance, and strategic data consulting roles.

6.SAS Certified Data Scientist Overview: Offered by SAS Institute, this certification focuses on using SAS tools and techniques for data manipulation, statistical analysis, and data visualization.

Benefits: Advanced Analytics Skills: Provides expertise in using SAS for complex data analysis and predictive modeling. Industry Recognition: SAS is widely used in industries such as finance, healthcare, and marketing, enhancing your career prospects. Practical Application: Demonstrates your ability to apply advanced analytics techniques to solve business problems.

7.Tableau Desktop Specialist Overview: Offered by Tableau, this certification focuses on the fundamentals of Tableau Desktop, including creating and sharing interactive data visualizations.

Benefits: Visualization Proficiency: Validates your ability to use Tableau for data visualization and business intelligence. Tool Familiarity: Tableau is a leading tool for data visualization, making this certification valuable for consulting roles. Career Opportunities: Enhances your ability to provide data-driven insights and reports to clients.

8.IBM Data Science Professional Certificate Overview: Offered by IBM on Coursera, this certification covers key data science skills, including data analysis, machine learning, and data visualization using IBM tools.

Benefits: Comprehensive Skillset: Provides a broad understanding of data science concepts and tools. Hands-On Experience: Includes real-world projects and practical experience with data science techniques. Career Entry: Suitable for those looking to enter the data science and consulting field with a strong foundational knowledge.

9.Data Science Council of America (DASCA) Certifications Overview: DASCA offers various certifications for data science professionals, including the Data Science Technician (DST) and Data Science Professional (DSP) certifications.

Benefits: Flexible Options: Offers different levels of certification based on your experience and career goals. Global Recognition: Recognized internationally, enhancing your credibility in the field of data science and consulting. Skill Validation: Validates your proficiency in data science concepts, tools, and techniques. By obtaining these certifications, you can demonstrate your proficiency in various aspects of data consulting, from data analysis and visualization to advanced data management and cloud-based solutions, positioning yourself for a successful career in this dynamic field.

 

Career & Jobs Back to Top

After completing the Career Path - Data Consultant course, which covers a wide array of topics including business intelligence, data analytics, programming languages, data visualization tools, and project management, individuals can pursue various roles in data consulting, analytics, and business intelligence. 

Here are typical job roles and potential salary ranges associated with this career path: 

1).Data Consultant / Data Analyst-Salaries for data consultants or data analysts can vary widely based on experience and industry. On average, data consultants can earn between $70,000 to $120,000 per year. 

2).Business Intelligence (BI) Developer- Salaries for BI developers typically range from $75,000 to $130,000 per year. 

3).Data Engineer-Salaries for data engineers can range from $90,000 to $150,000 per year. Cloud Data Analyst-Salaries for cloud data analysts typically range from $80,000 to $140,000 per year. 

4).Data Visualization Specialist-Salaries for data visualization specialists can range from $70,000 to $120,000 per year. 

5).Project Manager (Data Projects)-Salaries for project managers specializing in data projects can range from $90,000 to $160,000 per year. 

Data Scientist-Salaries for data scientists typically range from $100,000 to $180,000 per year. These salary ranges are approximate and can vary based on factors such as geographic location, industry sector (technology, finance, healthcare), specific skills and certifications (such as AWS or Azure certifications for cloud computing), years of relevant experience, and the size of the organization. Continuous learning, advanced certifications, and proficiency in emerging technologies can further enhance career prospects and earning potential in data consulting and analytics roles. 

 

 

Interview Questions Back to Top

Q1:How do Business Intelligence (BI) and Data Analytics contribute to strategic decision-making?           

Ans:BI and Data Analytics provide valuable insights by analyzing historical and current data to identify trends, patterns, and anomalies. BI tools help in generating reports and dashboards that visualize this data, making it easier for decision-makers to understand complex information. Data Analytics dives deeper into data to uncover actionable insights, which helps organizations make informed strategic decisions and optimize performance

 

Q2:What are the key benefits of cloud computing for data management and analysis?   

Ans:Cloud computing offers scalability, flexibility, and cost-efficiency. It allows organizations to scale their infrastructure according to demand without significant upfront investment. Cloud services provide access to powerful computing resources and storage, making it easier to manage and analyze large datasets. Additionally, cloud platforms often offer integrated analytics tools and facilitate collaboration by providing access to data from anywhere.

 

Q3:How does R programming facilitate data analysis?

Ans:R programming is specifically designed for statistical computing and data analysis. It provides a vast array of packages for data manipulation, statistical modeling, and visualization. R is known for its strong support for complex statistical analyses and its extensive ecosystem of packages, such as ggplot2 for data visualization and dplyr for data manipulation, making it a powerful tool for data analysis tasks.

 

Q4:What are the key features of Power BI that make it a popular choice for business intelligence?                                                      

Ans: Power BI is popular for its user-friendly interface, powerful data integration capabilities, and interactive visualizations. It allows users to connect to various data sources, create customized reports and dashboards, and perform advanced data analysis. Power BI's integration with other Microsoft products, such as Excel and Azure, and its ability to publish and share reports online, further enhance its appeal.

 

Q5:How would you use Power BI to move from basic reporting to advanced analytics?                         

Ans: To transition from basic reporting to advanced analytics in Power BI, start by mastering the fundamentals of data import, transformation, and basic visualizations. Progress to advanced features such as DAX (Data Analysis Expressions) for creating custom calculations, using Power Query for complex data transformations, and implementing advanced data modeling techniques. Incorporate machine learning models, custom visuals, and real-time data analysis to enhance your reports and dashboards.The dashboard’s accuracy and usability before publishing it for stakeholder review.

 

Q6:What role does SAS Business Intelligence play in data management and analysis?         

Ans:SAS Business Intelligence offers a suite of tools for data integration, analysis, and reporting. It provides capabilities for data mining, statistical analysis, and predictive modeling. SAS BI tools help organizations in making data-driven decisions by delivering insights through robust reporting and analytical capabilities. It also supports data visualization and dashboard creation, enabling users to gain a comprehensive understanding of their business data.

 

Q7:What are some common SQL queries you use with MySQL for data analysis?                                   

Ans: Common SQL queries for data analysis in MySQL include:

a) SELECT statements for retrieving data

b) JOIN operations for combining data from multiple tables

c) GROUP BY and HAVING clauses for aggregating and filtering data

d) ORDER BY for sorting results

e) WHERE clauses for applying conditions to data retrieval

f) Subqueries and CTEs (Common Table Expressions) for complex data manipulations and analyses.

 

Q8:What advanced features of Microsoft Excel are most useful for data analysis?                   

Ans: Advanced features of Microsoft Excel include PivotTables for summarizing and analyzing large datasets, advanced functions like VLOOKUP, INDEX, and MATCH for complex data lookups, and Data Analysis Toolpak for performing statistical analyses. Conditional formatting and charting tools enhance data visualization, while Power Query and Power Pivot extend Excel’s data manipulation and modeling capabilities.

 

Q9:How does Google Sheets support collaboration and data analysis compared to Excel?               

Ans: Google Sheets supports real-time collaboration by allowing multiple users to work on the same document simultaneously. It offers cloud-based access, which ensures that the most recent version is always available. While it may not have as many advanced features as Excel, Google Sheets provides essential data analysis tools, such as functions, pivot tables, and basic scripting through Google Apps Script, and integrates well with other Google Workspace applications.

 

Q10:How do project management fundamentals apply to business intelligence projects?                   

Ans: Project management fundamentals, such as defining project scope, creating a detailed project plan, and managing resources and timelines, are crucial for successful business intelligence projects. These principles help in ensuring that BI projects are delivered on time, within budget, and meet the desired objectives. Effective risk management and stakeholder communication are also essential to address challenges and align BI solutions with business goals.

 

Q11:How would you use Microsoft Project to manage a BI project from initiation to completion?                                                                                                                                             

Ans: To manage a BI project using Microsoft Project, start by creating a detailed project plan that includes defining project objectives, tasks, milestones, and deadlines. Use the Gantt chart view to schedule tasks and allocate resources effectively. Monitor project progress using tracking features, adjust timelines and resources as needed, and manage risks by identifying potential issues early. Utilize reporting features to provide stakeholders with regular updates on project status and outcomes.

 

Q12:What are the key leadership skills necessary for managing a BI team?                                                 

Ans: Key leadership skills for managing a BI team include effective communication, strategic thinking, and the ability to inspire and motivate team members. Strong decision-making skills and problem-solving abilities are crucial for addressing challenges and ensuring project success. Additionally, a leader should possess the ability to foster collaboration, manage stakeholder expectations, and drive a culture of continuous improvement and innovation within the BI team.

 

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Q1. What are the payment options?
A1. We have multiple payment options: 1) Book your course on our webiste by clicking on Buy this course button on top right of this course page 2) Pay via Invoice using any credit or debit card 3) Pay to our UK or India bank account 4) If your HR or employer is making the payment, then we can send them an invoice to pay.

Q2. Will I get certificate?
A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php

Q3. How long is the course access?
A3. All our video courses comes with lifetime access. Once you purchase a video course with Uplatz you have lifetime access to the course i.e. forever. You can access your course any time via our website and/or mobile app and learn at your own convenience.

Q4. Are the videos downloadable?
A4. Video courses cannot be downloaded, but you have lifetime access to any video course you purchase on our website. You will be able to play the videos on our our website and mobile app.

Q5. Do you take exam? Do I need to pass exam? How to book exam?
A5. We do not take exam as part of the our training programs whether it is video course or live online class. These courses are professional courses and are offered to upskill and move on in the career ladder. However if there is an associated exam to the subject you are learning with us then you need to contact the relevant examination authority for booking your exam.

Q6. Can I get study material with the course?
A6. The study material might or might not be available for this course. Please note that though we strive to provide you the best materials but we cannot guarantee the exact study material that is mentioned anywhere within the lecture videos. Please submit study material request using the form https://training.uplatz.com/study-material-request.php

Q7. What is your refund policy?
A7. Please refer to our Refund policy mentioned on our website, here is the link to Uplatz refund policy https://training.uplatz.com/refund-and-cancellation-policy.php

Q8. Do you provide any discounts?
A8. We run promotions and discounts from time to time, we suggest you to register on our website so you can receive our emails related to promotions and offers.

Q9. What are overview courses?
A9. Overview courses are 1-2 hours short to help you decide if you want to go for the full course on that particular subject. Uplatz overview courses are either free or minimally charged such as GBP 1 / USD 2 / EUR 2 / INR 100

Q10. What are individual courses?
A10. Individual courses are simply our video courses available on Uplatz website and app across more than 300 technologies. Each course varies in duration from 5 hours uptop 150 hours. Check all our courses here https://training.uplatz.com/online-it-courses.php?search=individual

Q11. What are bundle courses?
A11. Bundle courses offered by Uplatz are combo of 2 or more video courses. We have Bundle up the similar technologies together in Bundles so offer you better value in pricing and give you an enhaced learning experience. Check all Bundle courses here https://training.uplatz.com/online-it-courses.php?search=bundle

Q12. What are Career Path programs?
A12. Career Path programs are our comprehensive learning package of video course. These are combined in a way by keeping in mind the career you would like to aim after doing career path program. Career path programs ranges from 100 hours to 600 hours and covers wide variety of courses for you to become an expert on those technologies. Check all Career Path Programs here https://training.uplatz.com/online-it-courses.php?career_path_courses=done

Q13. What are Learning Path programs?
A13. Learning Path programs are dedicated courses designed by SAP professionals to start and enhance their career in an SAP domain. It covers from basic to advance level of all courses across each business function. These programs are available across SAP finance, SAP Logistics, SAP HR, SAP succcessfactors, SAP Technical, SAP Sales, SAP S/4HANA and many more Check all Learning path here https://training.uplatz.com/online-it-courses.php?learning_path_courses=done

Q14. What are Premium Career tracks?
A14. Premium Career tracks are programs consisting of video courses that lead to skills required by C-suite executives such as CEO, CTO, CFO, and so on. These programs will help you gain knowledge and acumen to become a senior management executive.

Q15. How unlimited subscription works?
A15. Uplatz offers 2 types of unlimited subscription, Monthly and Yearly. Our monthly subscription give you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews each month. Minimum committment is for 1 year, you can cancel anytime after 1 year of enrolment. Our yearly subscription gives you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews every year. Minimum committment is for 1 year, you can cancel the plan anytime after 1 year. Check our monthly and yearly subscription here https://training.uplatz.com/online-it-courses.php?search=subscription

Q16. Do you provide software access with video course?
A16. Software access can be purchased seperately at an additional cost. The cost varies from course to course but is generally in between GBP 20 to GBP 40 per month.

Q17. Does your course guarantee a job?
A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience. Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey!

Q18. Do you provide placement services?
A18. While our course is designed to provide you with a comprehensive understanding of the subject, we currently do not offer placement services as part of the course package. Our main focus is on delivering high-quality education and equipping you with essential skills in this field. However, we understand that finding job opportunities is a crucial aspect of your career journey. We recommend exploring various avenues to enhance your job search:
a) Career Counseling: Seek guidance from career counselors who can provide personalized advice and help you tailor your job search strategy.
b) Networking: Attend industry events, workshops, and conferences to build connections with professionals in your field. Networking can often lead to job referrals and valuable insights.
c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests.
d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin.
While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities.

Q19. How do I enrol in Uplatz video courses?
A19. To enroll, click on "Buy This Course," You will see this option at the top of the page.
a) Choose your payment method.
b) Stripe for any Credit or debit card from anywhere in the world.
c) PayPal for payments via PayPal account.
d) Choose PayUmoney if you are based in India.
e) Start learning: After payment, your course will be added to your profile in the student dashboard under "Video Courses".

Q20. How do I access my course after payment?
A20. Once you have made the payment on our website, you can access your course by clicking on the "My Courses" option in the main menu or by navigating to your profile, then the student dashboard, and finally selecting "Video Courses".

Q21. Can I get help from a tutor if I have doubts while learning from a video course?
A21. Tutor support is not available for our video course. If you believe you require assistance from a tutor, we recommend considering our live class option. Please contact our team for the most up-to-date availability. The pricing for live classes typically begins at USD 999 and may vary.
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