Case Study

# Rakuten Unifies a Fractured Data Landscape on OpenMetadata

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Companies that grow through many independent services end up with data scattered across as many catalogs. At Rakuten, each engineering team kept its own catalog in a spreadsheet, a Confluence page, or a bespoke web app, so no one had a shared view of what data existed or how the businesses related, and a data consumer could spend two to three months finding whether a dataset was even useful.

Learn how Rakuten's Data Platform team consolidated discovery, governance, and utilization for one of the world's largest digital ecosystems on OpenMetadata, replacing a patchwork of siloed catalogs with a single group-wide platform and laying the foundation for AI agents. Inside this case study:

*   How Rakuten replaced Excel, Confluence, and custom catalog apps with one group-wide platform, applying standard governance consistently across teams with data products, a glossary, and tagging
*   How the team expects dataset discovery to drop from two to three months to under an hour, and data utilization to rise from a 30-60% baseline toward 80% as businesses onboard
*   How Rakuten is building toward AI on the same foundation, from automatic description generation across thousands of tables to MCP integration so agents can query lineage to debug pipelines