Data Warehouse ETL Testing & Data Quality Management A-Z

ETL Testing and Data Quality Management for beginners with practical exercises and certificate of completion.

Created by : Rated :4.3 80941 views

Last Updated: 2022-04-22 05:04:35 English Course Type: Self Learning

Understand the basics of ETL/ELT testing
The importance of Data Quality within the Data Lifecycle
Learn the different types of ETL/ELT testing and Data Quality dimensions
Design a set of frequently used ETL/ELT and Data Quality regression tests
A comparison of Data Quality tools (Informatica, Talend, Oracle, SAS)
Perform database tests using queries and build database views to automate ETL/ELT testing and Data Quality monitoring
Data Quality Management and monitoring
Setting up a database connection to your visualization tool
Build Data Quality dashboards and reports

Learn the essentials of ETL Data Warehouse Testing and Data Quality Management through this step-by-step tutorial. This course takes you through the basics of ETL testing, frequently used Data Quality queries, reporting and monitoring. In this tutorial we will learn how to build database views for Data Quality monitoring and build Data Quality visualizations and reports!

..Learn to build data quality dashboards from scratch!

..Learn some of the most common mistakes made when performing ETL/ELT tests..

..Forget about manual ad-hoc ETL testing, learn more about automated ETL and data quality reports

The course contains training materials, where you can practice, apply your knowledge and build an app from scratch. The training materials are provided in an Excel file that you can download to your computer. Each module also ends with a short quiz and there is a final quiz at the end of the course.

After completion of this course, you will receive a certificate of completion.

Good luck and hope you enjoy the course.

Pre-requisites:

Basic knowledge of SQL
Some experience with Visualization tools would be helpful, but not required
Basic setup of database (PostgreSQL, Oracle) and visualization tool (Qliksense) is recommended

Course content:

The course consists of the following modules:

Introduction
What is ETL/ELT Testing and Data Quality Management?
Build database views for Data Quality Monitoring
Build dashboards for Reporting
Exercises
Final Quiz

Who should follow this course?

Students that want to learn the basics of ETL/ELT testing and Data Quality Management
Business Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examples
Software Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboards
Data Stewards and Managers considering to apply data quality standards within their organization

Some basic knowledge of SQL
Some basic knowledge of visualization tools is recommended, but not required
Database setup (PostgreSQL, Oracle, SQL Server etc.) is recommended
Visualization setup (Qlik, Spotfire, Microstrategy, Tableau, PowerBI etc.) is recommended

Students that want to learn the basics of ETL/ELT testing and Data Quality Management
Business Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examples
Software Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboards
Data Stewards and Managers considering to apply data quality standards within their organization

Section 1 : Introduction 5 Lectures 00:28:31
Lecture 1 :
Introduction Preview
Lecture 2 :
What is ETL/ELT Testing and Data Quality Management?
Lecture 3 :
Data Categories and Classifications
Lecture 4 :
Data Quality Rules and Dimensions
Lecture 5 :
Data Requirements and Test Design - Exercise
Section 2 : Data Quality and ETL Testing - Building Database Views 7 Lectures 00:31:46
Lecture 1 :
What are Database Views?
Lecture 2 :
View Data Quality Completeness - Exercise
Lecture 3 :
View Data Quality Uniqueness - Exercise
Lecture 4 :
View Data Quality Validity - Exercise
Lecture 5 :
View Data Quality Consistency - Exercise
Lecture 6 :
View Data Quality Integrity - Exercise
Lecture 7 :
View Data Profiling - Exercise
Section 3 : Data Quality and ETL Testing - Dashboards and Monitoring 7 Lectures 00:51:35
Lecture 1 :
Create a Database Connection
Lecture 2 :
Data Quality Completeness Dashboard - Exercise
Lecture 3 :
Data Quality Uniqueness Dashboard - Exercise
Lecture 4 :
Data Quality Validity Dashboard - Exercise
Lecture 5 :
Data Quality Consistency Dashboard - Exercise
Lecture 6 :
Data Quality Integrity Dashboard - Exercise
Lecture 7 :
Data Profiling & Summary Dashboard - Exercise
Section 4 : Final Quiz 1 Lectures
Lecture 1 :
Quiz
Quiz

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Lorenz De Smedt,

246775 Course Views

3 Courses

Hi there! Hi there. My name is Lorenz,Â I am aÂ BI consultant with several years of experience working as a developer, system engineer and functional analyst, mainly in the Business Intelligence domain. Working experience: I have worked for clients within theÂ Energy and FinancialÂ sector, and have been involved in theÂ roll-out of Business Intelligence and Data Warehouse projects and theÂ implementation of BI solutions. As an instructor, I want to share my knowledge and experience inÂ BI and Data Visualization software.Â During these courses, I will explain the basic concepts, but also tips and tricks for creating Visualizations and Reports that best suit your purpose orÂ the purpose of your end-user. Course topics: - Business Intelligence and Reporting - Extract, Transform, Load (ETL) and Automation - Data Visualization (Qliksense, Microstrategy, Spotfire) - Databases (Oracle, PostgreSQL) - Python, Bash/Shell scripting Course approach: Practice! On average each courseÂ consists of 4-8 modules.Â Each of the courses containÂ exercises at the end of the module, which allow you to practice. The courses heavily focus on exercises and practicing. If you would like to learn about one of these topics, please check out the available courses.