One of the major challenges that organizations face is the need for data catalog refresh. As developers create new pipelines, data scientists update existing tables, and business analysts create new dashboards, data assets change often. A database catalog should identify these changes and update itself when possible. It should also be updated through user interaction and governance actions. For example, a data catalog should allow users to set filters that allow it to retrieve data assets that match certain criteria. For this reason, it is vital that database catalogs include user interaction in their architecture.
Using a data catalog allows users to search for specific information by entering a keyword or filter. Moreover, many data catalogs are automatically sorted according to frequency of viewing. Additionally, these databases are connected to BI and analytics platforms, allowing you to view data in a single, unified view. All this leads to a better user experience, which in turn decreases the burden of data engineers. But even if you’re not working with BI or analytics tools, you can use a data catalog to access information.
The metadata for a customer record database includes column names, data types, and descriptions. This metadata helps analysts discover and categorize information. The metadata also includes the business logic used to compute columns. Using crowdsourced metadata means that knowledge from a community can become a shared data management resource. Data management and analysis are human activities, but using data catalogs makes them easier and more convenient to use. For example, a customer record database has columns named “customer,” and metadata for product attributes, which is useful for making decisions.
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