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Data Governance
Why Do Data Governance Implementations Fail?
Data governance fails from three compounding causes: weak sponsorship, compliance-only process, and stale catalogs, per Gartner and Forrester research.
Atlan staff
Emily Winks
Data Governance Expert
Emily Winks is a data governance expert who came to data through library and information science. Over 18+ years she has moved from children's librarian to information architect at WeWork to Atlan's Founder's Office, bringing a cataloging discipline to how enterprises classify, govern, and trust their data. She writes on data governance, enterprise data management, and the context layer.
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About Emily.
After graduating with a Master of Library and Information Science and a certificate in Records Management and Archives, Emily began her career as a children's librarian. After seven years in libraries she left to join the corporate workforce — she doesn't sing The Hokey Pokey (as often) anymore, but still puts her whole self in when it comes to navigating the ambiguities of data, making digital information clear, and empowering others to do the same.
She spent her library years at the Smithtown Special Library District and as a Senior Librarian at the New York Public Library before moving into information architecture. At WeWork she progressed from Information Architect to Senior Information Architect to Data Product Architect, building the classification and data structures behind a fast-scaling business.
Emily joined Atlan's Founder's Office in 2023, where she works at the intersection of data governance, enterprise data management, and the context layer — writing on how organizations classify, govern, and make their data trustworthy for both teams and AI agents.
Press, talks & code
Certifications & training
Recent articles by Emily Winks.
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- 02AI Agent Context Layer
Metadata Tooling Build vs Buy: Evaluation Criteria
Should you build metadata tooling in-house or buy a platform? Seven criteria enterprise architects can use to decide, plus what a fair RFP requires.
- 03AI Agent Data for AI
Build vs Buy a Knowledge Assistant: The Context Layer Underneath
Compare the real cost of building vs buying an internal knowledge assistant, including the ongoing burden of retrieval quality, permissions, and freshness.
- 04Knowledge Retrieval
RAG vs Context Layer for Internal Assistants: What Breaks
RAG can leak permissions and serve stale answers in internal knowledge assistants. See the four failure modes and when a context layer fixes them.
- 05AI Agents
Text-to-SQL with AI: How It Works and Where It Breaks
See how text-to-SQL AI turns natural language into SQL, why schema linking and join hallucination cause silent errors, and what guardrails production needs.
- 06Semantic Layer
Context Layer vs Data Catalog vs Semantic Layer: What Differs
A data catalog, semantic layer, and context layer solve different problems. See how they stack, when you need each, and where teams get it wrong.
- 07Data & AI
Text-to-SQL vs Semantic Layer for Self-Serve Analytics
Text-to-SQL vs semantic layer for self-serve analytics: see which pattern fits your use case, the governance risk each one hides, and why they converge.
- 08AI Context
What Is the Context Conference?
The Context Conference is Atlan's virtual event on AI context, October 28, 2026. See the agenda, who is speaking, and how it differs from Activate.
- 09Data Governance
AWS Glue and DataZone vs a Cross-Cloud Context Layer: What Survives the AWS Boundary
AWS shipped three documented exits from its native governance stack since November 2025. See what crosses the AWS boundary to a context layer and what…
- 10Data governance
Business Process and Policy Management Software: What It Governs, and What the Context Layer Has to Govern Instead
Business process and policy management software names two markets, not one. See what each one governs, where its reach ends, and what has to govern…
- 11Context Layer
DataZone vs Atlan: Where AWS-Native Governance Stops and a Context Layer Starts
Amazon DataZone catalogs and governs inside AWS. See where its automated context capture stops, when DataZone alone is enough, and how Atlan layers above it.
- 12Data Governance
AWS DataZone vs Glue Data Catalog: Which One Do You Need?
See how AWS DataZone and Glue Data Catalog differ, when AWS-native teams need one or both, and why AWS's new AI-agent fixes still stop at…
Transparency
Editorial relationship
Atlan staff byline
Emily is a member of the Atlan team. Articles published under her byline reflect her own analysis and expertise; Atlan's editorial team works with her on structure and clarity but does not author content attributed to her. She reviews and approves every piece published under her byline before publication.
Reach Emily