Duration 3 days – 21 hrs
Overview
This training focuses on building practical knowledge and hands-on skills in ETL Testing with a strong emphasis on Data Migration Testing. It covers essential concepts, testing techniques, and tools needed to test the extraction, transformation, and loading (ETL) of data between source and target systems. Participants will learn to validate massive data migrations with confidence—ensuring that business-critical information is accurately transferred between legacy systems and new platforms. To enhance the skills of QA professionals, data testers, and analysts in ETL and Data Migration Testing, enabling them to confidently validate data integrity, accuracy, completeness, and transformation during system upgrades, platform migrations, or large-scale data warehouse implementations.
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
