ETL Testing Course Overview

ETL Testing Course Overview

The ETL Testing course offers a comprehensive understanding of the testing processes involved in ensuring the quality of data integration, transformation, and loading. Primarily aimed at professionals in the field of data warehousing and business intelligence, the course equips learners with the skills needed to validate and verify data from various sources.

Module 1 sets the foundation by introducing ETL testing, exploring the lifecycle of ETL processes, and reinforcing database concepts, emphasizing the significance of ETL in Business Intelligence. It also covers the differences between OLTP and OLAP systems and the role of data warehousing.

In Module 2, the focus shifts to database and data warehousing testing, explaining RDBMS and relational database concepts while highlighting the unique aspects of data warehousing testing.

Module 3 dives deep into ETL testing scenarios, covering the data warehouse workflow, ETL mapping, and techniques for detecting data mismatches and losses.

Module 4 addresses the correctness, completeness, quality, and data validation aspects of ETL testing, including structure and constraint validation and negative testing approaches.

Module 5 empowers learners to perform data checks using SQL, offering insights into database structures and the utilization of SQL scripts for testing.

Lastly, Module 6 explores reports and cube testing, outlining the scope of Business Intelligence testing to ensure that reports accurately reflect data.

This course will be instrumental in helping learners master the art of ETL testing, thereby enhancing their capabilities in maintaining data integrity and quality in complex data environments.

Purchase This Course

USD

850

View Fees Breakdown

Course Fee 850
Total Fees
850 (USD)
  • Live Training (Duration : 16 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request
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♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

  • Live Training (Duration : 16 Hours)
  • Per Participant
  • Classroom Training fee on request

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

Request More Information

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Koenig's Unique Offerings

Target Audience for ETL Testing

The ETL Testing course offers comprehensive knowledge on data validation and troubleshooting within data warehousing, vital for IT professionals in database-related roles.


  • Data Analysts
  • Quality Assurance Professionals
  • ETL Developers
  • BI Specialists
  • Database Administrators
  • Software Testers
  • Data Warehouse Professionals
  • Project Managers (with a focus on data projects)
  • IT Graduates aspiring to specialize in data warehousing
  • Technical Consultants involved in data management projects
  • System Analysts
  • Data Scientists who require understanding of ETL processes


Learning Objectives - What you will Learn in this ETL Testing?

Course Introduction:

Gain proficiency in ETL testing and ensure data integrity in business intelligence systems. Learn to differentiate between databases, understand ETL scenarios, and validate data quality through hands-on SQL techniques and testing strategies.

Learning Objectives and Outcomes:

  • Understand the fundamentals of ETL testing and the lifecycle of the ETL process in a business intelligence context.
  • Grasp key database concepts with an introduction to RDBMS and relational database structures.
  • Differentiate between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems, and comprehend their roles in data warehousing.
  • Identify the nuances between database testing and data warehousing testing, including integrity constraints and their importance.
  • Explore various ETL testing scenarios, including ETL mapping and data warehouse workflow, to effectively manage data warehouse testing.
  • Learn how to test for data mismatches and data loss, ensuring the accuracy and integrity of the Data Migration process.
  • Master the testing of data correctness, completeness, quality, and structure through structure validation and constraint validation techniques.
  • Utilize SQL for data checks, learning to navigate database structures and execute SQL scripts for data validation purposes.
  • Develop skills in negative testing and understand its role in verifying system robustness and error handling capabilities.
  • Conduct comprehensive reports and cube testing within the scope of Business Intelligence testing, ensuring the reliability of BI reports and data visualizations.

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