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- On Saturday, July 27, 2019
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10 Top Metadata Management Tools
Metadata management solutions play a key role in managing data for organizations of all shapes and sizes, particularly in the cloud computing era.
This typically covers four primary areas: data analysis, data value, data governance, and risk and compliance.
These include metadata repositories, a business glossary, data lineage and tracking capabilities, impact analysis features, rules management, semantic frameworks, and metadata ingestion and translation.
In this Datamation article for metadata tools, we have identified 10 top vendors/tools: Jump to: Value proposition for potential buyers: The vendor’s Data Catalog solution delivers automated data inventory within a highly searchable catalog, along with a powerful recommendation engine.
Read user reviews of Alation Value proposition for potential buyers: Alex Solutions produces a marketplace for enterprise data through a robust and highly flexible data catalog, a customizable business glossary, intelligent tagging and policy driven data quality that takes place through detailed data profiling and machine learning.
Key values/differentiators: The vendor offers powerful data governance and cataloging capabilities designed to consume and manage data across an enterprise.
This includes a collaborative authoring environment that helps users create a central catalog of enterprise-specific terminology, including relationships to data assets, along with robust filters for understanding lineage and numerous data relationships.
Read user reviews of IBM Value proposition for potential buyers: Informatica delivers a comprehensive, unified view of metadata, business context, tagging, relationships, data quality, and usage.
The platform is designed for a wide array of users, including data analysts, data scientists, data stewards, and data engineers.
It includes tools for business, technical and operational metadata management, connectors, semantic search and browse, end-to-end data lineage, data relationship discovery, and impact analysis.
It ingests and analyzes diverse data in order to reveal targeted contextual data for tasks such as improving customer experience, contract lifecycle management, records management, data and text analytics, process automation, regulatory compliance, and information security.
- On Saturday, December 14, 2019
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