The enterprise data catalog market has seen significant changes in the modern AI era.
Traditional data catalogs functioned as static repositories where users sought datasets and documentation. The market evolved to incorporate data governance features, with many providers rebranding the technology as data intelligence platforms.
Initial AI enhancements to data catalogs were expected to transform data access, but often yielded unreliable outcomes that enterprises hesitated to rely on for vital decisions.
Today, a fresh wave of metadata-aware AI agents aims to close this gap, sustaining business context throughout conversations and offering the precision enterprises need.
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Alation, a major independent data intelligence platform vendor, boasts that 40% of the Fortune 100 are its clients, and has been progressively enhancing its AI capabilities as data requirements evolve.
Today the company unveiled its latest AI features, including an enhanced data query function named ‘Chat with Your Data,’ which claims to boost answer accuracy by up to 30%.
The shift in the data catalog market indicates a fundamental change in enterprise expectations. Organizations no longer want separate systems for data discovery, governance, and analysis. They require unified platforms that democratize data access while ensuring the accuracy vital for business-critical decisions.
“I believe generative AI impacts data management work and also emphasizes the importance of data management and application development,” Satyen Sangani, CEO and co-founder of Alation told VentureBeat.
Traditional data catalogs operated on a destination model. Users would navigate the platform, search for information, and browse through results. This model worked when data teams acted as intermediaries between business users and data systems.
“Previously, Alation was sold mainly to data management professionals,” Sangani said. “Increasingly, we’re seeing CIOs, CTOs, and CPOs who are developing technology and deploying it, using Alation to build agents while ensuring these agents are appropriately governed and managed.”
In essence, business users sought direct data access without needing technical expertise or analyst support. These users just want the necessary data and accurate answers without worrying about the complexities of the underlying data platforms, a gap where AI has a substantial impact.
“I think the world has been turned upside down, and I think chat is the new medium for self-service data, unlike the older catalog medium,” Sangani stated.
Alation’s strategy focuses on what Sangani terms a “knowledge layer” composed of curated data products and comprehensive metadata. Although Alation has developed its own data catalog and governance capabilities over the past decade, it recently acquired the privately-held startup, Numbers Station, to enhance its AI capabilities for data.
“Numbers Station essentially built agents on top of structured data,” Sangani explained. “They realized that agent development was more of a metadata and evaluation problem than an AI problem.”
Numbers Station’s technology is now an integral part of Alation’s new chat capabilities. This integration allows users to query their data through chat, making data more accessible and queryable at scale. The technology ensures the right metadata is available, evaluates the precision of agents, and provides accurate instructions and tuning for agents.
Competitive positioning in the data intelligence market
The traditional data catalog market is highly competitive.
Large data platform vendors such as Databricks and
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