“It’s impossible to overstate the value of getting your data right. With Informatica, our teams make well-informed decisions the first time around, which means better results for consumers, faster.”
Automate data discovery, curation and lineage
Find data across cloud and on-premises
Efficiently locate data assets and identify their content, structure and relationships for a complete view of data.
Enrich data with AI-powered curation
Add relevant context to data assets through automated classification, association and recommendations.
Understand relationships with data lineage
Explore asset relationships and analyze impact with automated, end-to-end data lineage.
Assess and monitor data quality
Automatically profile data, apply rules, identify issues and measure data quality via metrics & scorecards.
Collaborate and harness tribal knowledge
Share insights and enhance metadata with certifications, ratings, reviews, Q&A, workflows and notifications.
Pay only for what you use with our flexible pricing.
Explore related Data Catalog services
As a leading part of the AI-powered Informatica Intelligent Data Management Cloud (IDMC), Data Catalog works with a range of complementary services.
Key Data Catalog Resources
Meet the Experts: What’s New in Cloud Data Governance and Catalog
Cloud Data Governance and Catalog Adoption Guide: 8 Best Practices for Success
Deliver Data Intelligence with Cloud Data Governance and Catalog
Cloud Data Governance and Catalog
FAQ for Data Catalogs
A data catalog is a centralized inventory of data with information which describes that data (metadata) that helps organizations efficiently find and understand these assets. Data catalogs offer modern enterprises a way to harness the power of data for analytics and AI initiatives by curating it to raise data quality, classifying it for relevancy, and overall building its trustworthiness.
A data catalog is a centralized inventory of data with information which describes that data (metadata) that helps organizations efficiently find and understand these assets. Data catalogs offer modern enterprises a way to harness the power of data for analytics and AI initiatives by curating it to raise data quality, classifying it for relevancy, and overall building its trustworthiness.
A machine learning data catalog utilizes advanced algorithms and techniques to automate capabilities including data discovery, metadata extraction, data inventory, data classification, data curation and data lineage.
A data dictionary provides technical documentation, specification and description of data structures in a database including data attributes, fields, data type, length, valid values, default values etc. Whereas, a data catalog serves as a centralized repository of all data assets across the organization with search and management tools that enable data discovery, promote collaboration, and support data governance.
A data catalog allows organizations to connect to data sources, classify data types and inventory them; whereas a data marketplace provides the next step by packaging up these data sets into data products for end users to request, review and use for business initiatives by accessing them using a business-friendly portal.