From Hadoop to BigQuery: A Practical, Zero-Downtime Migration Playbook​

Legacy Hadoop-based data lakes struggle with scalability, cost, and operational complexity. In this session, I’ll walk through a real-world cloud data migration strategy for moving large-scale enterprise data lakes from Hadoop to Google BigQuery without downtime.

The talk covers:
- Designing parallel pipelines to ensure business continuity.
- Handling schema evolution and data validation at scale.
- Ensuring data quality and accuracy across millions of records.
- Optimizing performance and cost in a cloud-native analytics stack.

This session is grounded in hands-on enterprise experience supporting revenue analytics, reporting, and AI-driven use cases in production environments.

Learning Objective
By the end of this session, attendees will be able to:
- Design a zero-downtime data lake migration strategy
- Implement validation frameworks to ensure data accuracy post-migration
- Understand common pitfalls when modernizing Hadoop-based systems
- Apply cloud-native best practices for scalable analytics