📄️ NBA Data Modeling
Introduction to the NBA and Its Data Ecosystem
📄️ Building Metadata for NBA
The guidelines provided below outline best practices to follow when creating your own metadata or modifying existing metadata generated by the agent. Adhering to these practices ensures consistency, accuracy, and clarity in metadata management. This helps improve data discoverability and usability.
📄️ Building Semantics
Think of your data as a vast library of books. The schema is the library's cataloging system—the table of contents and index. It doesn't contain the data itself, but it provides a clear definition of every table (book) and column (chapter) in your data source.
📄️ Building Semantics
If the schema is your data's blueprint, the semantics layer is its brain. It adds the business context, logic, and human-friendly language needed to transform raw data columns into meaningful insights. The quality of your semantics directly depends on a well-defined schema.