Design a Scalable Data Model
Learn how to organize complex data into an easy-to-navigate star schema that makes analysis faster and smarter.
When we talked about where data lives—whether in a data warehouse or a lakehouse—we took a big step in understanding how data flows and is stored. Now, imagine you’re designing a map to navigate through all that stored data. This map helps data engineers and analysts find the answers they need without getting lost.
That’s where the star schema comes in. It’s like creating a well-marked star-shaped map for your data, making it easy to explore and analyze.
The star schema is also known as the
Enter the star schema
The star schema is one of the easiest and most popular ways to structure a data warehouse. It’s called a star because its layout looks like one—there’s a central table with several other tables branching out from it.
This schema helps us organize large amounts of data in a way that’s both clear and fast for analysis.
At its core, the star schema includes a central fact table and multiple dimensional tables that connect to it. This structure helps us ask powerful questions about our data without getting lost in complexity.
The fact table—center of our data model
Think of the fact table as the central point where all the action is tracked.
Every time someone buys a product, clicks a link, books a flight, or orders a burger, that moment is recorded in this table. It stores the measurable data: quantities, totals, amounts, and counts. These are our metrics, also known as facts.
Let’s say we’re running a coffee chain. ...