Build practical data quality and testing skills with ETL Testing Training, a comprehensive course designed for QA professionals, software testers, data engineers, database professionals, BI developers, and IT specialists who want to validate the accuracy and reliability of data across ETL pipelines.
Duration 3 days – 21 hrs
Overview
This ETL Testing Training provides practical, hands-on knowledge of ETL testing and Data Migration Testing, with a strong focus on validating data as it moves between source and target systems. Participants will learn how to test the extraction, transformation, and loading processes to ensure that business-critical data is transferred accurately, completely, consistently, and securely.
The course begins with the fundamentals of ETL and data migration, helping participants understand the ETL lifecycle, migration processes, source-to-target data mapping, and the role of testing throughout a data migration project. Learners will explore common challenges associated with migrating large volumes of data from legacy systems to new databases, applications, cloud platforms, and data warehouses.
Participants will develop practical skills in source-to-target validation, data reconciliation, data completeness testing, data integrity testing, transformation validation, and data quality testing. Using SQL and practical testing techniques, learners will learn how to compare source and target data, identify discrepancies, validate business rules, and detect missing, duplicate, inconsistent, or incorrectly transformed records.
The training also covers the creation of ETL test cases and test scenarios, test data preparation, defect reporting, root cause analysis, and regression testing. Participants will gain an understanding of commonly used ETL and data validation tools, including Informatica, Talend, SSIS, QuerySurge, and other data testing solutions, as well as the fundamentals of automating repetitive ETL tests.
Through hands-on exercises, real-world scenarios, and case studies, participants will learn how to approach ETL Testing and Data Migration Testing throughout the migration lifecycle—from pre-migration validation and testing during data transformation to post-migration verification.
By the end of the course, participants will be able to confidently validate large-scale data migrations and identify data quality issues before they affect business operations, reporting, analytics, or downstream applications. The training provides practical skills that can be applied to system upgrades, database migrations, cloud migrations, data warehouse implementations, and enterprise data integration projects.
Learning Objectives
- Understand the ETL lifecycle and its role in data migration.
- Design and execute test cases for data migration projects.
- Perform source-to-target data validation using SQL and testing tools.
- Identify data quality issues and transformation errors.
- Implement data reconciliation techniques and automate repetitive ETL tests.
- Apply industry best practices in Data Migration Testing scenarios.
Audience
- Quality Assurance (QA) Engineers and Testers
- Data Analysts and Data Migration Specialists
- Business Intelligence (BI) and Data Warehouse Professionals
- Database Administrators (DBAs)
- IT Professionals involved in system or platform migrations
Pre- requisites
- Basic understanding of databases and SQL
- General knowledge of software testing concepts
- Exposure to data warehousing or migration projects (preferred but not required)
Course Content
Module 1: Introduction to ETL and Data Migration
- What is ETL?
- Difference between ETL and Data Migration
- Types of data migration (Application, Storage, Database, Cloud)
- Migration lifecycle and where testing fits
Module 2: Data Migration Testing Fundamentals
- What is Data Migration Testing?
- Goals and challenges in data migration testing
- Types of migration testing: pre-migration, during migration, post-migration
- Key focus areas: data completeness, accuracy, integrity, and consistency
Module 3: ETL Testing Concepts
- ETL architecture in a migration context
- Common transformation and loading logic
- Types of ETL testing: smoke, functional, regression, performance
- Data mapping and test requirement analysis
Module 4: Writing Test Cases and Scenarios
- Identifying test data requirements
- Source-to-target mapping validation
- Writing SQL queries to validate data
- Creating reusable test templates and scripts
Module 5: Hands-on SQL for Validation
- Querying source and target systems
- Using joins, aggregations, and filters for comparisons
- Null/duplicate checks, record count verification, and data profiling
Module 6: Common ETL/Data Migration Tools
- Overview of ETL tools (Informatica, Talend, SSIS)
- Data validation tools (QuerySurge, Datagaps, etc.)
- Test automation basics in ETL testing
Module 7: Error Handling and Defect Management
- Identifying, reporting, and analyzing data mismatches
- Logging defects in migration projects
- Root cause analysis in data anomalies
Module 8: Best Practices and Case Studies
- Industry best practices in data migration testing
- Test data management techniques
- Real-world data migration testing scenarios and lessons learned
