Informatica Cloud Data Governance and Catalog

Data has become foundational to digital business, powering decisions from strategy to operations and enabling marketing automation, manufacturing automation, and AI/ML, which depend on large volumes of information. As data volumes and storage options have proliferated—especially through diverse cloud databases from major cloud service providers and big data analytics stacks—a key constraint has emerged: data that users cannot find or access has limited value. Regulatory pressures such as the EU GDPR reinforce the need to know where sensitive data like personally identifiable information resides, but the text emphasizes this as equally a business mandate: data can only be protected and exploited when it is known.

These demands, alongside “data democratization” (broader access to data across roles), drive adoption of three tightly related solution categories: metadata management (including lineage), data catalogs (central repositories enabling discovery and use), and data governance (control over usage and flow). Strong data management underpins cloud data sprawl control, compliance, consistent understanding of data, and governance and explainability for AI/ML.

Informatica’s Cloud Data Governance and Catalog extends its established data management portfolio with a cloud-native, SaaS, serverless offering within the Intelligent Data Management Cloud (IDMC), using consumption-based pricing. The solution builds a connected knowledge graph from extracted metadata, lineage, profiling, classification, business glossary linkage, and data quality. It supports multi-cloud and hybrid environments, provides rich search (including natural language-like search), user-centric views, metrics such as data quality ratings, and workflows for approvals and data quality tasks. It also governs AI models as catalog assets, documenting inputs/outputs and monitoring bias, drift, and performance with alert thresholds. Strengths include breadth, scalability, lineage, source coverage, and CLAIRE AI integration; challenges center on platform breadth, inherent governance complexity, and non-trivial onboarding of data sources—necessitating a clear roadmap, responsibilities, processes, and policies.

• AI and machine learning build on large amounts of data.
• Major cloud service providers such as AWS and Microsoft Azure offer more than 10 kinds of databases in some cases.
• The EU GDPR increases the need to know where personally identifiable information resides.
• Data catalogs store and manage enterprise metadata as a central repository spanning managed data stores.
• Metadata management includes data lineage capabilities that analyze and document flows between systems.
• Informatica Cloud Data Governance and Catalog is a cloud-native SaaS offering within the Intelligent Data Management Cloud.
• The offering uses a serverless deployment model designed for scale without prior server deployment.
• The solution can catalog and govern data across multiple clouds and integrate with both cloud and on-premises sources.
• The platform uses a connected knowledge graph to represent and link metadata for navigation.
• AI models can be governed as catalog assets, with bias and data drift tracked and alert thresholds configurable.

• “Data that is not known to the users and data that cannot be accessed is of little value.”
• “Data can only be used when it is known, and data can only be protected when it is known.”
• “Data Catalogs and Data Governance are the cornerstones of the modern, digital business.”
• “The goal is to deliver a comprehensive, cloud-based solution for managing metadata, Data Governance, and the Data Catalog.”
• “It operates using a serverless model, i.e., in a deployment model that is built for scale and does not require prior deployment of servers.”
• “All metadata is held in a ‘connected knowledge graph’.”
• “Search… includes capabilities such as natural language-like search, query generators, previews of data assets.”
• “Workflows… can be used to manage approvals to business glossary and terminology.”
• “A significant advantage… is that consumption of services can commence gradually.”
• “Despite strong capabilities, the effort required for connecting to data sources and adding them to the data catalog and data lineage must not be underestimated.”