Introduction
Cake includes connectors for BigQuery data. BigQuery, Google Cloud’s serverless, fully managed data warehouse, serves as the backbone of analytical data infrastructure, enabling teams to query massive datasets quickly, cost-effectively, and reliably. BigQuery abstracts away infrastructure management while delivering sub-second SQL performance over petabyte-scale data. It powers everything from business intelligence dashboards to machine learning feature stores, supporting decision-making and automation across engineering, product, and AI teams.
Use Cases
BigQuery plays a central role in:
Product and growth analytics: Serving as the source of truth for user behavior, engagement metrics, and retention dashboards.
Experimentation frameworks: Storing and analyzing A/B test results, feature flags, and control-treatment splits at scale.
Data preprocessing for ML: Generating and materializing feature tables used in training, evaluation, and real-time inference.
Data lineage and observability: Tracking pipeline outputs and integrating with tools like dbt, Superset, Metabase, and Looker for full visibility into the analytics layer.