To build an Iceberg lakehouse with BigLake, start by storing your data in Cloud Storage. Then, define this data using BigLake tables for Apache Iceberg. The BigLake metastore serves as your centralized, serverless catalog for these Iceberg tables, eliminating the need to manage complex infrastructure. This setup allows any Iceberg-compatible engine to consistently access and manage your data, creating a unified, open, and scalable lakehouse environment with ease.

You can use Apache Iceberg for evolving data lake datasets like transactions or market feeds. BigLake enables BigQuery to then query Iceberg tables alongside native storage without data movement. You can ingest real-time streams into BigQuery, combining with historical Iceberg data via BigLake for immediate, comprehensive analysis. BigQuery ML then generates real-time insights like market volatility and fraud detection as well as predictive models like credit risk and customer behavior.

BigLake provides secure, consistent access to a single copy of data in Cloud Storage. Dataplex Universal Catalog then automatically catalogs this data so all data users and engines can access. This ensures consistent data definitions, easy discovery, and unified governance, eliminating silos and fostering collaboration on one source of truth.