Explore a lakehouse

Activity overview
As a cloud data analyst, you'll likely encounter three main data architectures: data lakes, data warehouses, and lakehouses.

A data lake is a database system that stores large amounts of raw data in its original format until it’s needed. A guiding principle is to collect data first, and decide what is useful later.

A data warehouse is a database that consolidates data from multiple source systems for data consistency, accuracy, and efficient access. A guiding principle is to select and organize data that is known to be useful and can be trusted.

A lakehouse is a hybrid data architecture that combines the features of a data lake with those of a data warehouse.

Cloud Storage is a great tool for a data lake. BigQuery can be configured as a data warehouse, as a data lake, or as a lakehouse.

In this exercise, you'll combine data stored in a Cloud Storage data lake with data stored in a BigQuery data warehouse to learn more about how to integrate data from different sources and store it in a way that is optimized for analysis. Then, you'll explore this hybrid architecture to learn more about how lakehouses work.
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