Description
The modern data stack is evolving beyond proprietary, closed ecosystems toward open, interoperable architectures. At the center of this transformation is the open data lakehouse, where every layer—from ingestion (Airbyte), to storage (open-source object storage), to transformation (dbt), to querying (Dremio, DuckDB, Trino), and beyond—adheres to open standards.
This session will explore:
Why open standards matter: How openness fosters innovation, avoids vendor lock-in, and ensures long-term data portability.
Best practices for building an open data lakehouse: How to integrate Airbyte, Apache Iceberg, and cloud-native object storage for scalable, efficient data movement.
DataOps in an open ecosystem: Strategies for ensuring observability, governance, and performance across an open-source data stack.
Real-world use cases: How organizations are successfully adopting open data architectures to accelerate AI, analytics, and real-time decision-making.
By adopting an open data lakehouse approach, organizations gain greater flexibility, cost efficiency, and innovation potential, while ensuring that their data remains accessible and future-proof in an ever-changing data landscape.