A data catalog customarily has the following features.
The first step for building a data catalog is collecting the data’s metadata. Data catalogs use metadata to identify the data tables, files, and databases. The catalog crawls the company’s databases and brings the metadata (not the actual data) to the data catalog.
Data Management Platforms
Analytics and Business Intelligence Platforms
By looking at the profile of data consumers view and understand the data quickly. These profiles are informative summaries that explain the data.
For example, the profile of a database often includes the number of tables, files, row counts, etc.. For a table, the profile may include column description, top values in a column, null count of a column, distinct count, maximum value, minimum value and much more.
Data Lineage is a visual representation of where the data is coming from, where it moves and what transformations it undergoes over time. It provides the ability to track, manage and view the data transformation along its path from source to destination.
Hence, it enables the analyst to trace errors back to the root cause in the analytics.
Through this feature, data consumers can discover related data across multiple databases. For example, an analyst may need consolidated customer information. Through the data catalog, she finds that five files in five different systems have customer data. With a data catalog and the help of IT, one can have an experimental area where you can join all the data and clean it. Then one can use that consolidated customer data to achieve your business goals.