DataOps Training Series for QA: ETL Testing, Data Migration Testing, and Data Monitoring

Join Sandesh Gawande, CEO of iceDQ, in this in-depth webinar series designed to empower QA and data professionals with practical knowledge across the full DataOps lifecycle. As organizations increasingly rely on modern data architectures, the role of QA in ensuring data accuracy, scalability, and reliability has never been more critical.

This three-part series covers essential topics in ETL testing, cloud migration, and automation in data pipelines—equipping teams to address evolving challenges in data quality and operations.

Episode 1: Fundamentals of ETL & Data Warehouse Testing

Key Topics Covered:

1. What is ETL and Data Warehouse testing?
2. How DataOps applies to QA roles
3. Challenges in data testing vs. traditional QA
4. Legacy testing methods vs. rule-based ETL testing
5. Validation vs. reconciliation rules
6. Types of ETL tests
7. Real-world examples using the iceDQ platform

Episode 2: Cloud & Snowflake Data Migration Testing: Best Practices for QA

Key Topics Covered:

1. How to manage data consistency across hybrid systems
2. Strategies to detect and resolve data quality issues in large ETL pipelines
3. Techniques to avoid data loss and ensure compliance during migration
4. Rule-based validation & reconciliation methods tailored for Snowflake
5. End-to-end automation for high-volume migrations

Episode 3: DataOps for QA Teams: Automate Data Testing & Data Monitoring

Key Topics Covered:

1. Strategies to automate data testing and monitoring workflows.
2. Techniques to reduce manual effort and improve data reliability.
3. Insights into building scalable, repeatable DataOps processes.
4. Real-world examples of successful DataOps implementations for QA.

Whether you’re a seasoned QA expert or just stepping into the world of data testing, this webinar series will equip you with the tools, techniques, and real-world insights needed to thrive in modern DataOps environments.

Co-hosted by Innovate QA Events.