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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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().

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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

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.

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

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.

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.

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

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.

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.

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

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