---
title: "Learn with Atlan | Guides, Tutorials & Best Practices"
url: "https://atlan.com/know/"
description: "Search 1,000+ articles by topic - data governance, AI readiness, data catalogs, and modern data practices. Learn by topic; all content is free to read."
keywords: "data governance guides, data catalog tutorials, AI readiness, data management best practices, Atlan knowledge base"
---

> Atlan is hosting Context Conference, bringing together the leaders and builders at the frontier of giving AI the context it needs to understand their business. It runs online on October 28, 2026, from 11:00 AM to 2:00 PM ET. Atlan co-founder Prukalpa Sankar opens and closes the day. Leaders from AstraZeneca, BNY and Verizon share why they invest in context and what they get from it. Registrants get early access to The AI Context Gap, a new study from MIT Technology Review Insights. Register: https://atlan.com/context-conference/

Learn with Atlan is Atlan's library of articles and tutorials. "We're writing down everything we learn": articles, how-to guides, and resources on data governance, context engineering, enterprise AI and more. All content is free to read, searchable and filterable by category at [https://atlan.com/know/](https://atlan.com/know/).

Looking for downloadable guides, blueprints, or courses? See [Atlan's Resource Center](https://atlan.com/resources/).

## Categories

1770 articles in total. Categories with 10 or more articles: Ai Agent (351), Data Governance (276), Data Catalog (179), Customer Stories (70), Data Quality (60), Snowflake (48), Metadata Management (34), AI Readiness (32), Data Lineage (31), AI Agents (25), General (22), Gartner (20), Context Engineering (18), Microsoft Fabric (17), Apache Iceberg (17), Databricks (16), Data Mesh (16), AI Governance (15), Data Management (14), Data Observability (12), Data Discovery (12), Modern Data Stack (12), Data Team (12), Data Architecture (11), Data Orchestration (11), Data & AI (10), AI and Data Governance (10).

## Latest articles

- [Microsoft Purview Alternatives: Choosing The Right Data Governance Solution](https://atlan.com/purview-alternatives/) (Data Governance, 2026-10-13). Looking at Microsoft Purview for data governance? Here's what it provides within the Microsoft ecosystem - and how Atlan complements it.
- [What Is Writer AI? Enterprise Generative AI Platform [2026]](https://atlan.com/know/ai-agent/ai-agent-applications/what-is-writer-ai-enterprise-platform/) (Ai Agent, 2026-10-12). Writer is an enterprise agent platform with Palmyra models, Knowledge Graph, and Agent Builder. See its components, pricing, and integrations.
- [What Is Braintrust? How the AI Eval Platform Works in 2026](https://atlan.com/know/ai-agent/ai-agent-evals/what-is-braintrust/) (Ai Agent, 2026-10-12). Braintrust is an AI eval platform for tracing and scoring LLM agents. See how it works, what an eval score leaves open, and where context lineage helps.
- [Writer Knowledge Graph vs Enterprise Context Layer](https://atlan.com/know/ai-agent/context-layer/writer-knowledge-graph-vs-enterprise-context-layer/) (Ai Agent, 2026-10-12). Writer Knowledge Graph vs a governed enterprise context layer: what each grounds, where in-platform RAG stops, and how the two work together through MCP.
- [Atlan vs TrustGraph: Context Layer vs Self-Hosted Graph [2026]](https://atlan.com/know/ai-agent/knowledge-graph/atlan-vs-trustgraph/) (Ai Agent, 2026-10-12). Atlan vs TrustGraph compared: what TrustGraph's open-source context graph does, what Atlan's context layer adds, and how both work together in 2026.
- [What Is TrustGraph Used For in AI Pipelines? A 2026 Guide](https://atlan.com/know/ai-agent/knowledge-graph/what-is-trustgraph-used-for-in-ai-pipelines/) (Ai Agent, 2026-10-12). TrustGraph builds context graphs for GraphRAG and agents. See what it does in AI pipelines, where it stops, and when an enterprise context layer fits.
- [What Is an Operational Ontology? Objects, Links, and Actions](https://atlan.com/know/ai-agent/ontology/what-is-an-operational-ontology/) (Ai Agent, 2026-10-12). Learn how an operational ontology connects business objects to governed actions, how write-back works, and why AI agents need current context underneath it.
- [MCP and the Semantic Layer: How AI Agents Get Governed Metrics](https://atlan.com/know/ai-agent/semantic-layer/mcp-semantic-layer-for-ai-agents/) (Ai Agent, 2026-10-12). How MCP connects AI agents to a semantic layer's metric definitions, what a semantic layer's MCP server leaves out, and where a context layer fits.
- [Agent Context Layer Tools: The 2026 Directory](https://atlan.com/know/ai-agent/agent-context-layer-tools/) (Ai Agent, 2026-10-09). A structured directory of 17 agent context layer tools organized by use case: enterprise context, graph memory, RAG, and conversational memory for 2026.
- [The 13 Best AI Agent Evaluation Platforms in 2026](https://atlan.com/know/ai-agent/ai-agent-evals/best-ai-agent-evaluation-platforms/) (Ai Agent, 2026-10-09). Compare 13 AI agent evaluation platforms, including Braintrust, LangSmith, and Arize AX, on durability, trajectory depth, and pricing for 2026.
- [Feature Store for ML: How It Fits in the Modern AI Stack](https://atlan.com/know/ai-agent/data-for-ai/feature-store-for-ml/) (Ai Agent, 2026-10-09). A feature store solves training-serving skew and enables feature reuse across ML teams. Here is how it works and what governance layer belongs above it.
- [What is Genie Ontology? Databricks' live context layer](https://atlan.com/know/ai-agent/databricks/genie-ontology/) (Ai Agent, 2026-10-09). Genie Ontology is the Databricks live context layer, announced at DAIS 2026, that learns your business to power Genie with accurate answers at lower token cost.
- [AI Memory vs RAG vs Knowledge Graph: Enterprise Context Guide](https://atlan.com/know/ai-memory-vs-rag-vs-knowledge-graph/) (AI Architecture, 2026-10-09). AI memory, RAG, and knowledge graphs are layers of the same stack, not alternatives. Learn the composition pattern, when to use each, and what governs them all.
- [Best AI Agent Memory Frameworks in 2026: Mem0, Zep, LangChain, Letta Compared](https://atlan.com/know/best-ai-agent-memory-frameworks-2026/) (AI Agents, 2026-10-09). A comparison of the top AI agent memory frameworks in 2026 - Mem0, Zep, LangMem, Letta, and more - covering architecture, strengths, and enterprise fit.
- [Business Context for AI: What It Is and Why It's Missing](https://atlan.com/know/business-context-for-ai/) (Data Governance, 2026-10-09). Business context for AI is the org-specific layer agents need to act correctly. Learn what it is, why it's missing, and how governed metadata closes the gap.
- [What Is a Business Context Layer?](https://atlan.com/know/business-context-layer/) (General, 2026-10-09). What a business context layer is, why AI fails without it, and how to build one with governed definitions, ownership, metrics, and policies.
- [The context layer for AI: what makes one work](https://atlan.com/know/context-layer-for-ai/) (AI & Data Governance, 2026-10-09). A context layer for AI is the active infrastructure that delivers governed meaning, lineage, and policy to agents at decision time. See the 5 properties.
- [Databricks Data Compliance: Enhancing Native Features With A Unified Control Plane For Data](https://atlan.com/know/databricks/data-compliance-use-cases/) (Databricks, 2026-10-09). Databricks data compliance sets the rules every AI agent inherits, so answers built on Databricks data stay governed across AWS, Azure, and GCP.
- [How to Test Your AI Agent Harness](https://atlan.com/know/how-to-test-ai-agent-harness/) (AI Agent Engineering, 2026-10-09). Learn to test your AI agent harness with a six-layer stack: data validation, unit tests, integration, E2E simulation, adversarial testing, and CI/CD regression.
- [Knowledge Graphs vs RAG: Which Fits Your AI Stack?](https://atlan.com/know/knowledge-graphs-vs-rag-for-ai/) (AI Readiness, 2026-10-09). Knowledge graphs and RAG aren't rivals. See where each wins by query type, how GraphRAG combines them, and why your metadata decides if either works.
- [Ontology vs. Semantic Layer: What Data Teams Need in 2026](https://atlan.com/know/ontology-vs-semantic-layer/) (AI Readiness, 2026-10-09). Ontologies define domain concepts and relationships. Semantic layers map business logic onto data. Compare both and learn how Atlan connects them through a governed context layer.
- [17 Best Data Catalog Tools in 2026: A Complete Buyer's Guide](https://atlan.com/data-catalog-tools/) (Data Catalog, 2026-10-08). Compare the 17 best data catalog tools of 2026, the platforms powering enterprise discovery, governance, and context layer infrastructure for AI teams.
- [Best Data Catalogs for Microsoft Fabric (2026 Comparison)](https://atlan.com/best-data-catalogs-for-microsoft-fabric/) (Data Catalog, 2026-10-07). The best data catalogs for Microsoft Fabric, ranked: Purview is the native baseline, then Atlan, Collibra, Informatica, and Alation, scored on six criteria.
- [Coexist, Extend or Replace Purview: A Context Layer Framework](https://atlan.com/know/ai-agent/microsoft/coexist-extend-replace-purview/) (Ai Agent, 2026-10-07). Should you replace Microsoft Purview or keep it and add a catalog on top? Most teams coexist or extend; replace is narrow. A scorecard for deciding your path.
- [What Context Does Conversational Analytics on Power BI Depend On?](https://atlan.com/know/ai-agent/microsoft/power-bi-conversational-analytics-context/) (Ai Agent, 2026-10-07). See the verified F2+ capacity floor, the RLS-as-accuracy argument, the Q&A-to-Copilot dependency, and why one certified Power BI model isn't the whole estate.
- [Microsoft Purview Data Governance Coverage: Where It Stops](https://atlan.com/know/ai-agent/microsoft/purview-data-governance-coverage/) (Ai Agent, 2026-10-07). Microsoft Purview's data governance covers 20+ non-Microsoft sources, but depth varies by capability. See where policy, lineage, and file-share support stop.
- [Snowflake to Fabric Migration: Keeping Lineage Intact](https://atlan.com/know/ai-agent/microsoft/snowflake-to-fabric-migration-lineage/) (Ai Agent, 2026-10-07). Snowflake to Fabric migration often means running both, not a cutover. See what OneLake, Mirroring and Purview carry across, and what they still miss.
- [Synapse to Fabric Migration: Keep Metadata and Lineage Intact](https://atlan.com/know/ai-agent/microsoft/synapse-to-fabric-migration-metadata/) (Ai Agent, 2026-10-07). What Microsoft's Synapse to Fabric migration tools actually move, what metadata and lineage gaps open up, and how a context layer keeps definitions intact.
- [What Is Microsoft Purview?](https://atlan.com/know/ai-agent/microsoft/what-is-microsoft-purview/) (Ai Agent, 2026-10-07). Microsoft Purview is Microsoft's unified data security, governance, and compliance platform spanning 15 sub-products, licensed across M365 and Azure.
- [What Are Microsoft Fabric Data Agents?](https://atlan.com/know/microsoft-fabric/what-are-fabric-data-agents/) (Microsoft Fabric, 2026-10-07). Microsoft Fabric data agents are GA, read-only tools that turn questions into SQL, DAX, or KQL, and answer quality depends on the semantic model.
- [What Is Microsoft Fabric IQ?](https://atlan.com/know/microsoft-fabric/what-is-fabric-iq/) (Microsoft Fabric, 2026-10-07). Microsoft Fabric IQ explained: what its ontology, semantic models, Graph, and agents do, what's shipped versus still preview, and where a context layer fits.
- [Data Governance Councils in 2026: Setup, Roles & Tooling](https://atlan.com/data-governance-council/) (Data Governance, 2026-10-06). A data governance council sets policy and accountability for data and AI. Learn its responsibilities, members, a seven-step setup, and the tooling it needs.
- [6 Data Governance Examples for Modern Teams](https://atlan.com/data-governance-examples/) (Data Governance, 2026-10-06). Six data governance examples with named results: enablement, quality, security, integration, culture, and operations, and how each prepares data for AI agents.
- [Data Observability: Definition, Key Elements, and Benefits](https://atlan.com/data-observability-101/) (Data Observability, 2026-10-06). Data observability is the telemetry behind a trusted agent answer: the signals that show why output drifted and which upstream fix to apply.
- [Data Profiling: Techniques, Benefits, and Examples for 2026](https://atlan.com/data-profiling-101/) (Data Profiling, 2026-10-06). Data profiling is the diagnostic step before data gets used: understanding structure, quality, and relationships before analysis, integration, or AI.
- [Data Warehouse Governance: Quality, Security, and Compliance](https://atlan.com/governance/data-warehouse-governance/) (Data Governance, 2026-10-06). Data warehouse governance covers quality, security, access, and compliance for the warehouse agents and analysts query first. Components and best practices.
- [What Is Google ADK (Agent Development Kit)? A 2026 Guide](https://atlan.com/know/ai-agent/ai-agent-applications/what-is-google-adk/) (Ai Agent, 2026-10-06). Google ADK is an open-source framework for building, evaluating, and deploying AI agents. See its components, ADK 2.0 workflows, runtime, and Atlan fit.
- [Amazon Bedrock Knowledge Bases vs. External Data Catalog](https://atlan.com/know/ai-agent/aws/amazon-bedrock-knowledge-bases-vs-external-data-catalog/) (Ai Agent, 2026-10-06). Amazon Bedrock Knowledge Bases retrieve content for RAG, while a data catalog adds meaning through metadata. See where each stops and how agents use both.
- [Databricks Omnigent Agent Runtime: Architecture and Limits](https://atlan.com/know/ai-agent/databricks/databricks-omnigent-agent-runtime/) (Ai Agent, 2026-10-06). Learn how the Databricks Omnigent agent runtime works: server, runner, and UI, where hosts run, what Databricks manages, and the context it cannot supply.
- [Databricks Omnigent vs. Neutral Context Layer for AI Agents](https://atlan.com/know/ai-agent/databricks/databricks-omnigent-vs-neutral-context-layer/) (Ai Agent, 2026-10-06). Omnigent controls how AI agents run, while a neutral context layer controls what they know. See how Databricks Omnigent vs. a neutral context layer compare.
- [What Is Databricks Omnigent Meta-Harness?](https://atlan.com/know/ai-agent/databricks/what-is-databricks-omnigent-meta-harness/) (Ai Agent, 2026-10-06). Learn what the Databricks Omnigent meta-harness is, how its uniform API, policies, and server work, where it stops, and how a context layer fills the gap.
- [How to Connect an AI Coding Agent to a Data Warehouse With MCP](https://atlan.com/know/ai-agent/how-to-connect-ai-coding-agent-to-data-warehouse-mcp/) (Ai Agent, 2026-10-06). Learn how to connect an AI coding agent to a data warehouse MCP server. Compare vendor-managed and self-hosted options, then set auth and permission scope.
- [Microsoft Agent Framework vs. Other Agent Frameworks](https://atlan.com/know/ai-agent/microsoft/microsoft-agent-framework-vs-other-agent-frameworks/) (Ai Agent, 2026-10-06). Compare Microsoft Agent Framework with Strands, Google ADK, OpenAI Agents SDK, Claude Agent SDK, LangGraph, and CrewAI on languages, protocols, and hosting.
- [Data Compliance Management in Banking: Your 2026 Guide](https://atlan.com/know/data-governance/data-compliance-management-in-banking/) (Data Governance, 2026-10-06). Data compliance management in banking covers GDPR, BCBS 239, PCI DSS, DORA, and AML rules. Learn who owns it, the five steps, and the capabilities that hold up.
- [Data Governance Lifecycle: Key Stages & Core Capabilities](https://atlan.com/know/data-governance/data-governance-lifecycle/) (Data Governance, 2026-10-06). The data governance lifecycle keeps the policy, ownership, and quality AI agents inherit trustworthy. Five stages, core capabilities, and scaling.
- [Data Governance Performance Metrics: Key KPIs and How to Measure](https://atlan.com/know/data-governance/performance-metrics/) (Data Governance, 2026-10-06). Learn which data governance metrics to track, how to set a baseline and targets, and how to tell whether your governance program is working for AI.
- [Data Privacy Governance Framework: A 6-Step Guide](https://atlan.com/know/data-privacy-governance-framework/) (Data Governance, 2026-10-06). A data privacy governance framework is what an AI agent inherits before it can act: what is PII, which policy applies, who can access it, what is certified.
- [Apache Paimon vs. Apache Iceberg: 2026 Comparison Guide](https://atlan.com/know/iceberg/apache-paimon-vs-iceberg/) (Apache Iceberg, 2026-10-06). Apache Paimon vs Apache Iceberg compared on workloads, storage, schema evolution, and interoperability, plus what agents need on top of either format.
- [McKinsey Data Governance Framework: Components & Steps](https://atlan.com/mckinsey-data-governance-framework/) (Data Governance, 2026-10-06). What McKinsey's data governance article actually says, how to organize it into four practical components and five steps, and what its 2026 AI research adds.
- [What Are Microsoft Copilot Studio Agents?](https://atlan.com/know/ai-agent/ai-agent-applications/what-are-microsoft-copilot-studio-agents/) (Ai Agent, 2026-09-30). See how Microsoft Copilot Studio agents get built, published, priced in Copilot Credits, and governed through Microsoft Agent 365 and Purview in 2026.
- [Microsoft Agent Framework: What It Is, Does & Replaces](https://atlan.com/know/ai-agent/microsoft/agent-framework/) (Ai Agent, 2026-09-30). Microsoft Agent Framework unifies Semantic Kernel and AutoGen into one open-source SDK for AI agents. See its capabilities, status, and where context fits.
- [Microsoft Purview Unified Catalog: Features, Pricing & Limits](https://atlan.com/know/ai-agent/microsoft/purview-unified-catalog/) (Ai Agent, 2026-09-30). Microsoft Purview Unified Catalog governs whether a data asset is compliant. Agent grounding lives elsewhere, in Fabric IQ. See what each layer actually does.
- [Microsoft Data Governance Tools: What Are Your Options?](https://atlan.com/know/data-governance/microsoft-data-governance-tools/) (Data Governance, 2026-09-30). Microsoft data governance tools set the rules your AI agents inherit, so every answer drawn from Purview and beyond stays governed and trusted.
- [FabCon Europe 2026: Dates, Venue, Keynote, Passes and Schedule](https://atlan.com/know/microsoft-fabric/fabcon-europe-2026-guide/) (Microsoft Fabric, 2026-09-30). FabCon Europe 2026 runs Sept 28 to Oct 1 at the CCIB in Barcelona. See the day-by-day schedule, keynote, pass prices and sold-out status, travel, and hotels.
- [FabCon Europe 2026 Sessions by Role: Governance, Security, AI](https://atlan.com/know/microsoft-fabric/fabcon-europe-2026-sessions-by-role/) (Microsoft Fabric, 2026-09-30). FabCon Europe 2026 sessions on governance, security and AI agents, sorted by role, with times, session codes, five schedule clashes and Fabric IQ status.
- [Purview vs Unity Catalog: Comparison and Evaluation Guide](https://atlan.com/know/purview-vs-databricks-unity-catalog/) (Data Governance, 2026-09-30). Purview governs your full data estate. Unity Catalog governs your Databricks lakehouse. Learn how to make the best choice for your business with Atlan.
- [Microsoft Fabric Copilot: AI-Driven Insights & Workflow Automation](https://atlan.com/microsoft-fabric-copilot/) (Microsoft Fabric, 2026-09-30). Learn how Microsoft Fabric Copilot simplifies analytics, automates workflows, and empowers data-driven teams with AI-powered tools in 2025.
- [Microsoft Fabric Use Cases: How Enterprises Execute Them](https://atlan.com/microsoft-fabric-use-cases/) (Microsoft Fabric, 2026-09-30). Explore real-world Microsoft Fabric use cases for modern data teams. Is Microsoft Fabric suitable for enterprise use cases?
- [Microsoft Fabric: Unified Analytics Platform Guide](https://atlan.com/microsoft-fabric/) (Microsoft Fabric, 2026-09-30). Discover how Microsoft Fabric unifies data integration, engineering, warehousing, and AI in one SaaS platform. Learn architecture, pricing, use cases, and governance features.
- [Power BI Data Governance: Importance, Elements, Features & Implementation Approach](https://atlan.com/power-bi-data-governance/) (Data Governance, 2026-09-30). Power BI data governance sets the rules your AI agents inherit, so every report and answer drawn from your dashboards stays trusted and governed.
- [Evaluating a Governance Platform for Fabric: 20 Questions to Ask](https://atlan.com/know/ai-agent/microsoft/fabric-governance-evaluation-questions/) (Ai Agent, 2026-09-29). Evaluating a data governance tool for Microsoft Fabric? Use these 20 vendor questions and a scorecard to test lineage, security, and workflows first.
- [Microsoft Fabric Governance: What's Built In and What You Add](https://atlan.com/know/ai-agent/microsoft/microsoft-fabric-governance/) (Ai Agent, 2026-09-29). Microsoft Fabric governance runs on OneLake catalog and Purview. Here's what they cover natively, where coverage stops, and what a Microsoft-first estate adds.
- [Proving Fabric and Power BI Lineage in a Proof of Value](https://atlan.com/know/data-catalog/microsoft/fabric-lineage-proof-of-value/) (Data Catalog, 2026-09-29). What to test in a Fabric lineage proof of concept before you sign: connector choice, Scanner API mode, permissions, and a hop-by-hop Power BI test matrix.
- [Which Tools Support End-to-End Power BI Column-Level Lineage?](https://atlan.com/know/data-catalog/microsoft/power-bi-column-level-lineage/) (Data Catalog, 2026-09-29). See the five-hop chain from a Fabric source table to a Power BI visual, the four settings for page-level lineage, and why it stops before Snowflake or Synapse.
- [Fabric Database Agent vs. Data Agent: What's the Difference?](https://atlan.com/know/microsoft-fabric/fabric-database-agent-vs-data-agent/) (Microsoft Fabric, 2026-09-29). Fabric data agent vs database agent: what each one does, GA vs early-access status, read-only vs monitor-and-act scope, and where operations agents fit.
- [Fabric IQ vs. Work IQ vs. Foundry IQ: 3 Context Sources, Not One](https://atlan.com/know/microsoft-fabric/fabric-iq-vs-work-iq-vs-foundry-iq/) (Microsoft Fabric, 2026-09-29). Fabric IQ vs Work IQ vs Foundry IQ compared on scope, release status, identity, and billing, plus why an agent sees only the IQs you wire in.
- [Who Governs a Fabric Item an Agent Created, Not a Person?](https://atlan.com/know/microsoft-fabric/who-governs-agent-created-fabric-items/) (Microsoft Fabric, 2026-09-29). Who governs agent created Fabric items? What Microsoft documents on CI/CD, MCP permissions, and audit logs, and the review step your team still has to define.
- [Data Classification and Tagging: What AI Agents Need](https://atlan.com/data-classification-and-tagging/) (Data Governance, 2026-09-28). Data classification and tagging set the labels an AI agent inherits, so every action it takes respects sensitivity, policy, and access before it runs.
- [Data Governance Standards: What to Adopt and How to Enforce Them](https://atlan.com/data-governance-standards/) (Data Governance, 2026-09-28). Data governance standards are the rules an AI agent inherits: what quality, security, and access require before it is allowed to act on an asset.
- [How to Evaluate an AI Readiness Platform in 2026](https://atlan.com/know/ai-agent/ai-readiness-platform-evaluation/) (Ai Agent, 2026-09-28). Evaluate an AI readiness platform by testing context, certification, runtime delivery, traceability, and portability, not a one-time readiness score.
- [RAG Pipeline vs. Context Layer: What Custom Retrieval Costs](https://atlan.com/know/ai-agent/rag-pipeline-vs-context-layer-tco/) (Ai Agent, 2026-09-28). See how RAG pipeline vs. context layer total cost of ownership breaks down across engineering, maintenance, permissions, evaluation, and scale for AI teams.
- [ROI of AI Agent Governance: Governed vs. Ungoverned Access](https://atlan.com/know/ai-agent/roi-of-ai-agent-governance/) (Ai Agent, 2026-09-28). Calculate the ROI of AI agent governance: faster deployment, less review and rework, reusable context, and lower failure exposure from governed access.
- [Context Engineering vs. Semantic Layer: What Each Does](https://atlan.com/know/ai-agent/semantic-layer/context-engineering-vs-semantic-layer/) (Ai Agent, 2026-09-28). Context engineering vs. semantic layer: compare what each one actually does, how they work together, and what your AI agents need first to run well.
- [What Questions Should You Ask About Governing Fabric AI Agents?](https://atlan.com/know/microsoft-fabric/fabric-ai-agent-governance-questions/) (Microsoft Fabric, 2026-09-28). Questions to ask about governing Fabric AI agents: ontology preview status, refresh and staleness, data reach, agent permissions, and who owns the context.
- [What Fabric's Own MCP Servers Actually Let an Agent Do](https://atlan.com/know/microsoft-fabric/fabric-mcp-servers/) (Microsoft Fabric, 2026-09-28). Every Microsoft Fabric MCP server mapped: Core, local, Fabric IQ, Ontology, and Real-Time Intelligence, with status, sign-in, and audit coverage.
- [What Is OneLake Catalog? Discover, Govern, Secure](https://atlan.com/know/microsoft-fabric/onelake-catalog/) (Microsoft Fabric, 2026-09-28). What is OneLake catalog? See what the Explore, Govern, and Secure tabs do in Microsoft Fabric, what is GA or preview, and how AI agents search it via MCP.
- [What Are Microsoft Purview's Controls for AI Agents?](https://atlan.com/know/microsoft-fabric/purview-controls-for-ai-agents/) (Microsoft Fabric, 2026-09-28). Purview controls for AI agents, from Microsoft's own docs: DSPM's agent inventory, preview prompt DLP for Copilot, Agent 365 identity, and coverage by surface.
- [What Are Translytical Task Flows in Microsoft Fabric?](https://atlan.com/know/microsoft-fabric/translytical-task-flows/) (Microsoft Fabric, 2026-09-28). Translytical task flows let a Power BI report write to Fabric data or call an API. How they work, status by data source, limits, and the agent-loop angle.
- [Open Source Data Governance Tools: 2026 Guide & Comparison](https://atlan.com/open-source-data-governance-tools/) (Data Governance, 2026-09-28). Open source data governance tools set the rules an AI agent inherits, compared by architecture, lineage, and what it actually takes to run one.
- [MCP Gateway vs. Context Layer: What's the Difference?](https://atlan.com/know/ai-agent/mcp-gateway-vs-context-layer/) (Ai Agent, 2026-09-25). An MCP gateway routes and authorizes calls. A context layer governs whether the answer behind that call is correct. See how the two compose in AI agent stacks.
- [MCP Gateway vs. Single MCP Server: When Do You Need One?](https://atlan.com/know/ai-agent/mcp-gateway-vs-single-mcp-server/) (Ai Agent, 2026-09-25). MCP gateway vs. single MCP server: the spec-grounded thresholds for team count, tool count, and compliance that tell you when a gateway earns its overhead.
- [When Do You Need a Formal MCP Registry vs. Ad Hoc MCP Usage?](https://atlan.com/know/ai-agent/mcp-registry-vs-ad-hoc-mcp-usage/) (Ai Agent, 2026-09-25). See when a formal MCP registry beats ad hoc MCP usage, the signals that mark the line, and why the official MCP Registry still isn't enough on its own.
- [Public vs. Private MCP Server Registry: Which Do You Need?](https://atlan.com/know/ai-agent/public-vs-private-mcp-server-registry/) (Ai Agent, 2026-09-25). The official MCP Registry does not support private servers. See when a public, private, or hybrid MCP server registry fits your team, with real examples.
- [What Is an MCP Gateway?](https://atlan.com/know/ai-agent/what-is-an-mcp-gateway/) (Ai Agent, 2026-09-25). Learn what an MCP gateway is, how aggregator, proxy, and composite patterns work, and when you actually need one instead of a single MCP server.
- [What Is an MCP Registry? Server.json, Namespaces & Trust](https://atlan.com/know/ai-agent/what-is-an-mcp-registry/) (Ai Agent, 2026-09-25). An MCP registry catalogs Model Context Protocol servers via server.json and reverse-DNS namespaces. See how the official MCP Registry works, and what it skips.
- [AI Readiness Assessment: Scoring Your Data Estate for Agents](https://atlan.com/know/ai-agent/data-for-ai/ai-readiness-assessment/) (Ai Agent, 2026-09-23). Most AI readiness assessments return a number nobody can act on. Score the data estate per question, with evidence instead of self-report, on five dimensions.
- [AI-Ready Data Checklist: 12 Checks You Can Actually Fail](https://atlan.com/know/ai-agent/data-for-ai/ai-ready-data-checklist/) (Ai Agent, 2026-09-23). Most AI-ready data checklists cannot be failed. These 12 audit checks each have a pass condition and the artifact that proves it, scored per question.
- [What Makes Data AI-Ready? The Five Layers That Decide](https://atlan.com/know/ai-agent/data-for-ai/what-makes-data-ai-ready/) (Ai Agent, 2026-09-23). AI-ready data is decided one question at a time, not one table. See the five layers that decide whether an agent returns your answer or the average one.
- [DataHub Data Contracts: How They Work and Where They Fit](https://atlan.com/datahub-data-contracts/) (Data Quality, 2026-09-22). DataHub data contracts bundle schema, freshness and quality assertions into one producer commitment. See how they work, what they enforce, and where they stop.
- [Amazon Bedrock Knowledge Bases: Types, Deployment and Limits](https://atlan.com/know/ai-agent/aws/amazon-bedrock-knowledge-bases/) (Ai Agent, 2026-09-22). Amazon Bedrock Knowledge Bases ground agents in your own documents. See the two types, how ingestion works, what each costs, and where retrieval stops helping.
- [DataHub OpenLineage Support: How It Works and When to Use It](https://atlan.com/know/ai-agent/data-for-ai/datahub-openlineage-support/) (Ai Agent, 2026-09-22). DataHub OpenLineage support covers a REST endpoint and a Spark listener plugin. See what each path captures, where they differ, and what neither one carries.
- [Power BI Semantic Models Explained: 2026 Guide](https://atlan.com/know/ai-agent/semantic-layer/power-bi-semantic-model/) (Ai Agent, 2026-09-22). A Power BI semantic model holds tables, DAX measures and security roles. See what it contains, how storage modes work, and where AI agents hit its edges.
- [Top Alation Alternatives in 2026: A Complete Comparison Guide](https://atlan.com/alation-alternatives/) (Data Catalog, 2026-09-21). Evaluating Alation alternatives and competitors in 2026? This independent guide compares the top 10 options: Atlan, Collibra, Purview, CastorDoc, & more.
- [Alation Data Catalog Adoption in 2026: What the Deployment Matrix Decides](https://atlan.com/alation-data-catalog-adoption-challenges/) (Data Catalog, 2026-09-21). Alation's deployment matrix puts five capabilities, including its AI features, on Cloud Service only. That and three other documented tradeoffs, from Alation's own docs.
- [Alation vs. Collibra vs. Informatica: Should You Choose Any of These Platforms in 2026?](https://atlan.com/alation-vs-collibra-vs-informatica-vs-atlan/) (Data Catalog, 2026-09-21). See how Alation, Collibra, and Informatica compare in governance, lineage, automation, and adoption - and which platform fits modern enterprise needs.
- [Amundsen Alternatives - DataHub, Metacat, and Apache Atlas](https://atlan.com/amundsen-alternatives/) (Data Catalog, 2026-09-21). Amundsen was archived in September 2026. Compare DataHub, OpenMetadata, Metacat, Apache Atlas, and Atlan as the platforms to move to.
- [Understanding Amundsen Data Catalog: Architecture, Features & Installation](https://atlan.com/amundsen-data-catalog/) (Amundsen Data Catalog, 2026-09-21). Amundsen, Lyft's open-source data catalog, was archived in September 2026. Read its architecture, features, and the open-source options still maintained. 
- [Setting Up Amundsen Data Lineage with dbt: A 2026 Guide](https://atlan.com/amundsen-data-lineage-set-up/) (Data Lineage, 2026-09-21). Amundsen was archived in September 2026. How to set up Amundsen data lineage with dbt: metadata extraction, and lineage at the table and column levels.
- [Amundsen Demo: Explore Amundsen in a Pre-configured Sandbox Environment](https://atlan.com/amundsen-demo/) (Data Catalog, 2026-09-21). Amundsen was archived in September 2026. This pre-configured demo environment shows Lyft's open-source data catalog as it stood at that point, loaded with sample data.
- [Lyft Amundsen Data Catalog: Open Source Data Discovery Tool](https://atlan.com/amundsen-lyft-open-source-data-catalog/) (Amundsen Data Catalog, 2026-09-21). Lyft's Amundsen started the open-source data catalog category and was archived in September 2026. Its origin story, architecture, and how it worked.