Data catalog tools automate the discovery of data sources across an enterprise’s systems, enable search and track data lineage. Many also include data governance capabilities and enable self-service by business users.
A good data catalog tool also provides a Business Glossary with internal definitions of business terms so that users have a common understanding of data. It should also support data lineage visualizations for a more accurate view of historical data flows and transformations.
Modern data catalog tools provide AI-supported auto-tagging capabilities that can help classify unstructured datasets. They also offer version control tracking so that users can monitor changes over time.
These solutions allow stewards to flag inaccuracies and highlight data quality issues before they pollute their data lake or warehouse. They can even stop data from being loaded if they identify a critical error.
Some of these solutions can also help users discover data assets in their data environment by enabling natural language searches. They may also have collaboration features to allow people to chat and share information, work together on data workflows and review data assets.
Another useful feature is metadata management capabilities. This includes the ability to create custom metadata attributes for enriching data sets. These can be things like business department, technical steward, certified data set or any other relevant terms that you feel are important for your organization.
Most of these modern data catalog tools rely on artificial intelligence and machine learning capabilities to automatically catalog, organize, analyze and score data. They also provide a variety of other functions such as pattern detection, relationship discovery and pervasive profiling that allow users to quickly spot errors and start applying corrective actions.
