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Premium Career Track - Chief Data Officer (CDO)

This program consists of courses that will help you acquire skills to aim for CDO position in a reputed organization. Learn data strategy & analytics.
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Course Duration: 600 Hours
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This Premium Career Track - Chief Data Officer (CDO) program by Uplatz includes the following courses:

1. Talend

2. SAP Data Services (BODS)

3. SQL Programming with MySQL Database

4. Business Intelligence Specialization

5. Power BI

6. Tableau

7. SAS BI

8. Data Visualization in Python

9. Data Visualization in R

10. Build your Career in Data Science

11. Data Science with Python

12. Data Science with R

13. Machine Learning (basic to advanced)

14. Deep Learning Foundation

15. Generative AI Specialization

16. CISSP (Cybersecurity)

17. MS Excel

18. Google Sheets

19. Cloud Computing Basics

20. SAP MDG (Master Data Governance)

 

The Chief Data Officer (CDO) is a senior executive responsible for managing and leveraging an organization's data assets to drive strategic decisions, business growth, and operational efficiency. The role of the CDO has become increasingly important with the rise of data-driven decision-making and the recognition of data as a valuable corporate asset.

 

What does a CDO do?

A Chief Data Officer supports good data operations or DataOps. DataOps is an emerging concept that takes a process-oriented, automated, and collaborative approach to design, implementing, and managing data workflows and a distributed data architecture.

A CDO oversees the collection, management, and storage of data across an organization. They are responsible for analyzing and deriving insights from data to inform business strategy and value. Chief data officers form part of a company's executive team.

 

Roles and Responsibilities of a CDO

Overseeing data management, data analytics, and data governance

Ensuring data quality

Spearheading data and information strategy

Create a data management system that facilitates the secure collection and processing of data.

Establish a culture within your organization that normalizes sharing this data and making informed decisions on how to improve future business outcomes.

Implement proper data analytics to identify and, hopefully, reduce pain points at all stages of the business process, increasing not only profit, but also trust in the eyes of stakeholders and clients.

Course/Topic 1 - 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 2 - SAP Data Services (BODS) - all lectures

  • SAP BO Data Services consists of a UI development interface, metadata repository, data connectivity to source and target system and management console for scheduling of jobs. This introductory tutorial gives a brief overview of the features of SAP BODS and how to use it in a systematic manner.

    • 1:41:26
  • In this beginner's SAP BODS tutorial, you will learn, History of SAP BODS, SAP Data Services Advantages and the disadvantages of SAP BODS.

    • 1:37:53
  • SAP BODS is an ETL tool for extracting data from disparate systems, transform data into meaningful information, and load data in a data warehouse. It is designed to deliver enterprise-class solutions for data integration, data quality, data processing and data profiling.

    • 1:44:34
  • Data Services Designer is a developer tool, which is used to create objects consisting of data mapping, transformation, and logic. It is GUI based and works as a designer for Data Services.

    • 1:39:01
  • SAP BO Data Services (BODS) is an ETL tool used for data integration, data quality, data profiling and data processing. It allows you to integrate, transform trusted data-to-data warehouse system for analytical reporting.

    • 1:45:08
  • This tutorial will help all those students who want to create their own local repository, configure a job server, start basic job development and execute the job to extract data from source systems and load the data to target systems after performing transformations, look-ups and validations.

    • 1:38:08
  • This tutorial will help all those readers who want to create their own local repository, configure a job server, start basic job development and execute the job to extract data from source systems and load the data to target systems after performing transformations, look-ups and validations.

    • 1:29:13
  • Learn SAP Business Objects Data Services from basic concepts to advanced concepts starting from introduction, architecture, data services, file formats, data loading, etc.

    • 1:49:55
  • SAP BODS (Business Object Data Services) is an SAP DWH (Data Warehouse) product, where DWH is an enterprise level centralized reporting system. Data services is an end-to-end data integration, Data management, Test analysis software.

    • 1:54:16
  • Before you start this SAP BODS tutorial, you should have a basic knowledge of SAP system, RDBMS, Data warehouse and Business Intelligence (BI).

    • 1:52:00
  • SAP Bods training tutorials as per syllabus wise so beginners can easily learn SAP Business Object Data Services (Bods) step by step with real time project scenarios.

    • 1:37:31
  • SAP BODS combines industry data quality into one platform. BODS provides a single environment for development, run-time, management, security, and data connectivity.

    • 1:27:31
  • SAP BODS is an ETL tool that delivers a single enterprise-class solution for data integration, data quality, and data profiling that permits you to integrate, transform, improve, and provide trusted data that supports important business processes and enables sound decisions.

    • 1:37:14
  • It provides a GUI that allows us to efficiently produce a job that mine data from various sources, convert that data to meet the business requirements of an organization, and load data into a single place.

    • 1:43:07
  • SAP BO Data Services (BODS) is an ETL tool used for data integration, data quality, data profiling and data processing. It allows you to integrate, transform trusted data-to-data warehouse system for analytical reporting.

    • 1:29:54

Course/Topic 3 - 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 4 - Business Intelligence Specialization - all lectures

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

    • 1:20:10
  • In this tutorial we learn about business Intelligence, as a technological concept, which began shortly after the 1988 international conference, The Multiway Data Analysis Consortium, held in Rome. The conclusions reached at this conference jump-started efforts for simplifying BI analysis, while making it more user-friendly.

    • 2:42:42
  • In this lecture session we learn about The general process of business intelligence is as follows: Gathering data and organizing it through reporting. Turning it into meaningful information through analysis. Making actionable decisions aimed at fulfilling a strategic goal.

    • 1:03:39
  • In this lecture session we learn that Data Warehousing may be defined as a collection of corporate information and data derived from operational systems and external data sources and also talk about features of data warehousing.

    • 1:45:30
  • In this lecture session we learn about Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions.

    • 1:36:03
  • In this tutorial we learn about Apache HTTP Server is a free and open-source web server that delivers web content through the internet. It is commonly referred to as Apache and after development, it quickly became the most popular HTTP client on the web.

    • 1:10:35
  • In this lecture session we learn about NoSQL is an approach to database management that can accommodate a wide variety of data models, including key-value, document, columnar and graph formats. A NoSQL database generally means that it is non-relational, distributed, flexible and scalable.

    • 1:48:46
  • In this lecture session we learn about basic introduction of data analytics and also talk about features and functions of data analytics.

    • 1:07:03
  • In this lecture session we learn about Embedded BI (business intelligence) is the integration of self-service BI tools into commonly used business applications. BI tools support an enhanced user experience with visualization, real-time analytics and interactive reporting.

    • 1:03:54
  • In this lecture session we learn about Designing a collection strategy is one way to ensure that your accounts receivable stays under control and you continue to collect your cash. Without one, there is disorganization, disconnections, miscommunications and just simply chaos in the accounts receivable department.

    • 59:47
  • In this tutorial we learn about Survival analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and failure in mechanical systems.

    • 1:08:06
  • In this lecture session we learn about Geospatial analysis is the gathering, display, and manipulation of imagery, GPS, satellite photography and historical data, described explicitly in terms of geographic coordinates or implicitly, in terms of a street address, postal code, or forest stand identifier as they are applied to geographic models.

    • 1:23:43
  • In this lecture session we learn about Data mining is used to explore increasingly large databases and to improve market segmentation. By analyzing the relationships between parameters such as customer age, gender, tastes, etc., it is possible to guess their behavior in order to direct personalized loyalty campaigns.

    • 1:47:09
  • In this lecture session we learn about It is the simplest unsupervised learning algorithm that solves clustering problems. K-means algorithm partitions n observations into k clusters where each observation belongs to the cluster with the nearest mean serving as a prototype of the cluster.

    • 1:08:09
  • In this lecture session we learn about Density-based spatial clustering of applications with noise (DBSCAN) is a well-known data clustering algorithm that is commonly used in data mining and machine learning.

    • 1:32:29
  • In this lecture session we learn about Regression analysis is a reliable method of identifying which variables have impact on a topic of interest. The process of performing a regression allows you to confidently determine which factors matter most, which factors can be ignored, and how these factors influence each other.

    • 43:19
  • In this lecture session we learn about machine learning techniques in business intelligence and also talk about features and function of machine learning techniques in brief.

    • 1:12:20
  • In this lecture session we learn about machine learning is the necessary piece for truly self-service BI tools. BI tools with machine learning implementations not only enable deeper insights into data, but they also empower business people to take analysis into their own hands.

    • 2:34:07
  • In this lecture session we learn about Predictive analytics combining several data analysis techniques, such as machine learning, data mining, and statistics.

    • 1:47:14
  • In this lecture session we learn about Crowdsourced data collection is a participatory method of building a dataset with the help of a large group of people. This page provides a brief overview of crowdsourced data collection in development and highlights points to consider when crowdsourcing data.

    • 1:56:04
  • In this lecture session we learn about basic introduction to business analysis and also talk about features and functions of business analysis.

    • 1:46:49
  • In this tutorial we learn about Data models define how the logical structure of a database is modeled. Data Models are fundamental entities to introduce abstraction in a DBMS.

    • 1:01:32
  • In this lecture session we learn about deep dive into data warehousing and also talk about some key features of deep dive data warehousing.

    • 2:22:58
  • In this lecture session we learn about how we reduce the development time to market and also talk about common patterns in deep dive into data warehousing and also talk about features of patterns.

    • 53:34
  • In this lecture session we learn about basic introduction to data warehousing and also talk about features of data warehousing.

    • 1:33:00
  • In this lecture session we learn about Feature extraction for machine learning and deep learning. Feature extraction refers to the process of transforming raw data into numerical features that can be processed while preserving the information in the original data set. It yields better results than applying machine learning directly to the raw data.

    • 1:57:04
  • In this lecture session we learn about Integration Platform as a Service (iPaaS) is a suite of cloud services enabling development, execution and governance of integration flows connecting any combination of on premises and cloud-based processes, services, applications and data within individual or across multiple organizations.

    • 1:00:53
  • In this lecture session we learn about Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights.

    • 1:48:15
  • In this lecture session we learn about Contextual analysis is the systematic analysis—identification, sorting, organization, interpretation, consolidation, and communication—of the contextual user work activity data gathered in contextual inquiry, for the purpose of understanding the work context for a new system to be designed.

    • 1:17:25
  • In this lecture session we learn about Organizational intelligence is the capacity of an organization to create knowledge and use it to strategically adapt to its environment or marketplace. It is similar to I.Q., but framed at an organizational level. While organizations in the past have been viewed as compilations.

    • 1:36:55