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  • 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
View More...
  • Section 1 : Introduction 5 Lectures 00:28:31

    • Lecture 1 :
    • 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,

Hi there! Hi there. My name is Lorenz, I am a 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 the Energy and Financial sector, and have been involved in the roll-out of Business Intelligence and Data Warehouse projects and the implementation of BI solutions. As an instructor, I want to share my knowledge and experience in BI and Data Visualization software. During these courses, I will explain the basic concepts, but also tips and tricks for creating Visualizations and Reports that best suit your purpose or 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 course consists of 4-8 modules. Each of the courses contain 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.
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