At long last, we've arrived at the top of the data stack. For these final pages, we consider what makes a data mart. That is, we discuss how to further structure and group data in your warehouse not only to meet one set of needs, but to meet the needs of a number of departments whose business logic may differ from one another.
Stage 4: Data Marts
More data and more schemas will eventually make the data warehouse difficult to navigate. A data mart is a filtered (and sometimes aggregated) subsection of a data warehouse that makes it easier for a particular group to query data. It provides a smaller schema with only the relevant tables for that group.
Overview of Building Data Marts
For warehouses, we needed a warehouse lead to implement the modeling. For data marts, we'll need multiple mart leads. They will determine which tables from the data warehouse are needed for their individual marts (Figure P.1). The mart leads can then customize tables for different use cases. Aggregations, metric calculations, and PII can all be handled individually for teams. However, if there is a metric that needs to be used by multiple teams, the warehouse lead should implement it on the data warehouse.
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