Data catalog

It serves as a single source of truth for information about data sources, their lineage, quality, and usage. 

Data catalogs typically include metadata such as data definitions, ownership, classification, and access controls used for data quality management. 

They help organizations improve data governance, enhance data quality, and facilitate data discovery and reuse.

Data catalog vs data dictionary 

Data catalogs and data dictionaries are the tools used to manage and document data assets, but they serve different purposes. 

Data catalogs provide a comprehensive overview of an organization’s data assets, including metadata such as data definitions, ownership, classification, and access controls. 

Data dictionaries, on the other hand, focus on defining the structure and content of specific data elements, such as data types, formats, and constraints. 

While data dictionaries are often included within data catalogs, data catalogs offer a broader scope of information about an organization’s data landscape.

What are popular data catalog tools? 

Data catalogs are essential in helping organizations manage and govern their data assets. 

Below, we examine the most popular data catalog tools available on the market. Each of those offers unique features and capabilities and should be assessed with specific business needs in mind. 

• IBM InfoSphere Data Catalog: a comprehensive data catalog solution that offers features like data lineage, profiling, and governance.
• Collibra: a flexible and scalable data catalog platform that can be customized to meet specific organizational needs.
• Alation: a data catalog platform that provides insights into data usage, quality, and lineage.
• Erwin Data Intelligence: a data modeling and data cataloging tool that offers features like data profiling, impact analysis, and data quality assessment.

Talend Data Catalog: a data integration and quality platform that includes data cataloging capabilities.