Atlan Data Governance

Atlan data catalog

Atlan's catalog harvests metadata, adds a glossary, certification and data products, and uses Context Agents to write descriptions.

Compare: data catalog tools

• Data Catalog: Core product with 200+ connectors, Enterprise Data Graph, AI-powered search, asset certification, and a data marketplace (docs).

• Automated Metadata Harvesting: 200+ native connectors automatically extract schema, table, column, and pipeline metadata from databases, warehouses, BI tools, and ETL systems (website).

• Search & Discovery: Federated search across all catalog assets with faceted filtering by owner, classification, domain, and certification status (docs).

• AI-Powered Search: Natural language search powered by AI lets users find assets without knowing technical names — conversational queries across the full catalog (docs).

• Usage & Popularity Statistics: Usage analytics derived from warehouse query logs surface query frequency, unique user counts, and popularity rankings per asset (docs).

• Custom Fields & Templates: Custom metadata attributes and persona-based templates allow domain teams to define additional metadata fields beyond the default schema (docs).

• Asset Certification: Certificates (Verified, Draft, Deprecated, or none) on any asset, usable as a filter on the Assets page (docs).

• Business Glossary: Glossaries with terms, categories, and subcategories in a hierarchy, bulk upload or CSV import, manual term-asset links, and an app that links terms to matching assets automatically (docs).

• Metadata Propagation: Playbooks can automatically propagate classifications, tags, and descriptions from parent assets to related downstream assets when rules trigger (docs).

• Catalog Usage Analytics: Asset-level usage analytics confirmed; catalog-wide governance program adoption dashboards were not explicitly confirmed (website).

Atlan data lineage

Atlan shows column-level and end-to-end lineage across warehouses, pipelines and BI, with impact analysis.

Compare: data lineage tools

• Data Lineage: End-to-end, column-level lineage across databases, warehouses, ETL tools, and BI platforms via OpenLineage and native connectors (website).

• Table-Level Lineage: Dataset-to-dataset dependency mapping across all connected data sources (website).

• Column-Level Lineage: Column-level lineage is captured automatically, tracing every upstream and downstream dependency of a column across warehouses, pipelines, and BI tools; SQL is parsed from Snowflake, BigQuery, Redshift, and dbt (docs).

• End-to-End Lineage: Complete data journey from source systems through transformations to BI dashboards — spanning warehouse, ETL, and BI layers (website).

• Impact Analysis: Lineage-based impact analysis identifies all downstream assets affected by upstream changes — enabling confident change management (website).

• OpenLineage Support: OpenLineage connectors for Airflow, MWAA, Astronomer, Cloud Composer, Spark, and Flink send events to an Atlan endpoint, which catalogs DAGs and tasks as they run (docs).

Atlan data stewardship

Compare: data stewardship tools

• Data Stewardship: Governance workflows and the inbox route metadata changes, access requests, and new glossary terms and tags to owners for approval, with auto-approval rules for owners (docs).

• Review & Approval Workflows: No-code governance workflow templates (change management, data access, new entity creation, policy compliance) require all approval conditions to pass before a change is applied, with activity logs (docs).

• Governance Campaigns: Atlan's automation engine supports bulk governance operations — assigning ownership, propagating tags, and certifying asset groups — across domain workspaces (docs).

• Metadata Automation: Playbooks provide no-code, trigger-based automation for metadata enrichment, classification propagation, ownership assignment, and governance workflows (docs).

• Critical Data Elements: Not explicitly confirmed as a dedicated CDE feature in docs reviewed (website).

• Governance Scorecards: Not explicitly confirmed in product pages reviewed (website).

Atlan data classification

Compare: data classification tools

• Sensitive Data Discovery: Automated classification engine detects PII, PHI, PCI, and confidential data via ML classifiers and pattern matching — classifications are first-class citizens with propagation support (website).

• Data Policy: Policy Center enforces access controls, row-level and column-level security, and persona-based usage rules on data assets (docs).

• Native Policy Enforcement: Classifications (PII tags, security labels, compliance flags) propagate downstream through lineage and synchronize bi-directionally with Snowflake and Databricks, so governance is enforced in the platform rather than only recorded in the catalog (website).

• Data Masking: Column-level masking policies enforced via Personas and Purposes — masking PII fields for unauthorized consumers at query time (docs).

Atlan AI features

Atlan's Context Agents write documentation at scale, and its MCP servers let your own agents query the catalog.

• AI Features: AI-powered search, AI documentation generation, context agents for metadata enrichment, and an AI assistant all confirmed (docs).

• AI Chat Assistant: AI assistant for natural language catalog queries and data discovery — allowing users to find and understand data assets conversationally (docs).

• AI Documentation Generation: AI-generated descriptions for tables and columns at catalog ingestion — accelerating enrichment of newly discovered assets (docs).

• Agentic Metadata Enrichment: Context agents autonomously classify, tag, link, and enrich metadata at scale — applying governance rules without requiring manual review of each asset (docs).

Atlan data compliance

• Data Compliance: Immutable audit trail, regulatory workflow support, and access provisioning via Immuta for Snowflake/Databricks confirmed (website).

• Audit Trail: Immutable audit trail tracking all metadata changes, policy edits, and governance actions for regulatory evidence (docs).

• Compliance Reporting: Not explicitly confirmed as a dedicated compliance reporting feature (website).

• Regulatory Framework Mapping: GDPR-relevant classification and policy workflows exist, but explicit mapping of assets to regulatory frameworks was not confirmed (website).

• Data Activity Monitoring: Source-system data access monitoring (DAM) was not found in product pages reviewed (website).

• ROPA: GDPR workflows exist but a dedicated GDPR Article 30 processing register was not confirmed (website).

• Data Retention Policies: Not confirmed in product pages reviewed (website).

• Data Subject Rights: No DSAR automation or right-to-be-forgotten workflows confirmed (website).

Atlan collaboration

• Collaboration: Inline discussions, annotations on assets, Jira/ServiceNow ticketing, and Slack/Teams notifications confirmed (docs).

• Alert Notifications: Slack and Microsoft Teams integration for governance event notifications — surfacing catalog alerts where teams work (docs).

• Discussions & Annotations: Inline comments and threaded discussions anchored to tables, columns, and glossary terms — creating a searchable knowledge layer on catalog assets (docs).

• Ticketing Integrations: Jira and ServiceNow integrations for routing governance access requests and tasks to external issue-tracking systems (docs).

Atlan data marketplace

Compare: data marketplace tools

• Data Marketplace: Dedicated Data Marketplace for self-service data discovery, access requests, and consuming governed data products (website).

• Self-Service Access Requests: No-code workflow builder handles access requests end-to-end — routing through approval chains and provisioning access automatically via Immuta in Snowflake/Databricks (website).

• Data Products: First-class data products with ownership, schema contracts, quality guarantees, and versioning — published in the marketplace for consumer discovery (website).

• Data Mesh Support: Atlan explicitly supports data mesh — domain workspaces with independent ownership, federated governance, and data product publishing from domain teams (docs).

• Subscription Management: Change notifications and subscriptions to data products were not found in product pages reviewed (website).

Atlan data quality

Compare: data contracts tools

• Data Quality: Data quality monitoring with assertions, DQ rules, and quality signal aggregation — native DQ capabilities plus integrations with external DQ tools (docs).

• SQL Table Tests: Data quality rules and assertions at the table and column level — including custom SQL-based checks — available via native quality features (docs).

• Anomaly Detection: Anomaly detection on Snowflake tables through Atlan data quality (Snowflake only) (docs).

• Data Contracts: Contracts are a first-class feature — producer-consumer agreements specifying schema structure, quality expectations, and ownership with automated enforcement (docs).

• Data Health Scores: DQ signals are present but a dedicated composite health score per asset was not explicitly confirmed (docs).

• Data Profiling: Some column statistics are surfaced, but dedicated data profiling as a standalone feature was not explicitly confirmed (docs).

Atlan AI governance

• AI Governance: Dedicated AI Governance capability — registers AI models, model versions, and AI applications, manages their lifecycle from creation to retirement, enforces governance policies against organizational and regulatory standards, and assesses AI asset risk (docs).

• AI Asset Inventory: Provides comprehensive visibility into all AI assets — models, model versions, and applications — with lifecycle tracking from creation to retirement. Note: Request Data Access workflows are unsupported for AI assets; Data Products are the documented workaround (docs).

• AI Agent Access Governance: Agents query the lineage graph via the MCP server and receive provenance, quality scores, governance policies, and ownership in a single call before accessing data. Context Engineering Studio generates test suites from existing dashboards and queries that surface policy violations — agents using unauthorized data or missing required classifications — before production (website).

• AI Lineage: AI models are registered as governed assets and Atlan describes lineage that makes every agent decision auditable, but lineage from training data to a model is not documented (docs).

• AI Regulatory Compliance: AI Governance offers generic risk assessment — 'evaluate and assess risks associated with AI assets' — but the docs name no EU AI Act, NIST AI RMF or ISO 42001 framework mapping or evidence workflow (docs).

• AI Model Health Score: Visibility, lifecycle management, risk assessment and policy enforcement are covered, but no composite trust or health score is computed per model (docs).

Atlan workflows

• Workflows: API, MCP server, Python SDK (pyatlan), dbt integration, OpenLineage, and Playbooks automation all confirmed (docs).

• REST / GraphQL API: REST and GraphQL APIs for programmatic read/write of catalog metadata — comprehensive developer API with full CRUD operations (docs).

• MCP Server: Atlan MCP server (hosted, no infrastructure required) exposes catalog search, lineage, metadata updates, glossary management, and data quality to AI agents (docs).

• dbt Integration: Native dbt manifest ingestion for models, sources, tests, and column-level lineage — dbt assets are first-class catalog citizens (docs).

• Python SDK: pyatlan is the official Python SDK (pip install pyatlan) for programmatic interaction with the Atlan API (docs).

• Browser Extension: Chrome and Edge extension shows Atlan context inside BI tools and other apps, deployable through MDM (docs).

• Webhooks: Admin > Webhooks sends metadata events to any URL, signed with a secret (docs).

Atlan data context layer

• Knowledge Graph: Enterprise Data Graph explicitly models the entire metadata estate as a property graph — nodes for assets, users, terms, and policies; edges for all relationship types (website).

• Semantic Models: Context Layer / Context Engineering Studio generates machine-readable semantic context linking business glossary terms to physical SQL-queryable assets for AI and BI consumption (website).