ETL Testing: From Beginner to Expert

Course Curriculum

Chapter 1: Welcome! Thank you for learning the ETL Testing Course with me!

Lecture 1: Welcome! Thank you for learning the ETL Testing Course with me!

Chapter 2: Before we start

Lecture 1: What is Data Testing/ETL Testing and the Challenges in ETL testing?

Lecture 2: What will be the future of ETL tools/testing as big data is getting popular?

Chapter 3: The Basics – Data warehouse Concepts course

Lecture 1: Master Data Warehouse Concepts, Step by Step from Scratch

Lecture 2: Is Data Warehouse still relevant in the age of Big Data?

Lecture 3: What is Data?

Lecture 4: Why Data Warehouse is implemented?

Lecture 5: What is a Data Warehouse?

Chapter 4: Data Mart

Lecture 1: What is a Data Mart?

Lecture 2: Fundamental difference between Data Warehouse and Data Mart

Lecture 3: Advantages of a Data Mart

Lecture 4: Characteristics of a Data Mart

Lecture 5: Disadvantages of a Data Mart

Lecture 6: Mistakes and Misconceptions of a Data Mart

Chapter 5: Data Warehouse Architectures

Lecture 1: Revised: Enterprise Architecture or Centralized Architecture

Lecture 2: Revised: Federated Data Warehouse Architecture

Lecture 3: Multi Tired Architecture

Lecture 4: Components of a Data Warehouse Architecture

Lecture 5: Purpose of a Staging Area in Data Warehouse Architecture – Part 1

Lecture 6: Purpose of a Staging Area in Data Warehouse Architecture – Part 2

Chapter 6: Dimensional Modeling

Lecture 1: What is Data Modeling?

Lecture 2: Why should a Tester know Data Modeling?

Lecture 3: Data Modeling Techniques

Lecture 4: ER Data Model

Lecture 5: Dimensional Model

Lecture 6: Differences between ER Model and Dimensional Model

Chapter 7: How to build a Dimensional Model?

Lecture 1: Different phases required to build a Dimensional Data Model

Lecture 2: Business Requirements

Lecture 3: CDM – Conceptual Data Model

Lecture 4: LDM – Logical Data Model

Lecture 5: Physical Data Model

Lecture 6: Database

Chapter 8: Various Objects in a Dimensional Model

Lecture 1: What is a Dimension Table?

Lecture 2: What is a Fact Table?

Lecture 3: Additive Facts

Lecture 4: Semi Additive Facts

Lecture 5: Non-Additive Facts

Lecture 6: Fact less Facts

Lecture 7: What is a Star Schema?

Lecture 8: What is a Snow Flake Schema?

Lecture 9: Galaxy Schema or Fact Constellation Schema

Lecture 10: Snow Flake Vs Star Schema

Lecture 11: Conformed Dimensions

Lecture 12: Junk Dimensions

Lecture 13: Degenerate Dimensions

Lecture 14: Role Playing Dimensions

Lecture 15: Slowly Changing Dimensions – Intro and Example Creation

Lecture 16: Slowly Changing Dimensions (SCD) Type 1, 2, 3

Lecture 17: Slowly Changing Dimensions – Summary

Chapter 9: Data Integration and ETL

Lecture 1: What is Data Integration?

Lecture 2: What is ETL?

Lecture 3: Data Acquisition

Lecture 4: Data Transformation

Lecture 5: Common Questions and Summary

Chapter 10: ETL Vs ELT

Lecture 1: ETL – Explained

Lecture 2: ELT – Explained

Lecture 3: ETL Vs ELT

Chapter 11: Typical Roles In DWH Project

Lecture 1: Project Sponsor

Lecture 2: Project Manager

Lecture 3: Functional Analyst or Business Analyst

Lecture 4: SME – Subject Matter Expert

Lecture 5: DW BI Architect and Data Modeler

Lecture 6: DWH Tech Admin

Lecture 7: ETL Developers

Lecture 8: BI OLAP Developers

Lecture 9: ETL Testers / QA Group

Lecture 10: DB UNIX Network Admins

Lecture 11: Data Architect, Data Warehouse Architect, BI Architect and Solution Architect

Lecture 12: Final Note about the Roles

Chapter 12: DW/BI/ETL Implementation Approach

Lecture 1: Different phases in DW/BI/ETL Implementation Approach

Lecture 2: Knowledge Capture Sessions

Lecture 3: Requirements

Lecture 4: Architecture Phase

Lecture 5: Data Model/Database

Lecture 6: ETL Phase

Lecture 7: Data Access Phase

Lecture 8: Data Access Types – Selection

Lecture 9: Data Access Types – Drilling Down

Lecture 10: Data Access Types – Exception Reporting

Lecture 11: Data Access Types – Calculations

Lecture 12: Data Access Types – Graphics and Visualization