Secoda Data Catalog

Secoda data catalog

Secoda's catalog harvests metadata, with search, a glossary, a Verified tag and a Chrome extension.

Compare: data catalog tools

• Data Catalog: Full data catalog platform with automated metadata harvesting, search, documentation, lineage, and governance across the modern data stack (docs).

• Automated Metadata Harvesting: 100+ integrations automatically sync metadata from warehouses, BI tools, databases, and transformation tools on a scheduled or continuous basis (docs).

• Search & Discovery: Unified search across all connected data assets with filters, relevance ranking, and AI-assisted query understanding (docs).

• AI-Powered Search: Secoda AI answers natural language questions about data assets using the catalog as context — search returns AI-curated responses (docs).

• Usage & Popularity Statistics: Query usage statistics and popularity signals surfaced per table — identifies which assets are most queried (docs).

• Custom Fields & Templates: Custom metadata properties and documentation templates configurable per asset type (docs).

• Asset Certification: The Verified tag stamps approved resources and boosts them in search (docs).

• Catalog Usage Analytics: Workspace analytics dashboard and a weekly email for admins (docs).

• Business Glossary: Each Team has its own glossary; terms take a definition, owner, tags, synonyms, and verification status, can be nested under parent terms, and can use templates (docs).

• Metadata Propagation: Propagation copies properties to related resources, and automations can run it (docs).

Secoda data lineage

Secoda shows table, column and end-to-end lineage with impact analysis.

Compare: data lineage tools

• Data Lineage: Automated column-level and table-level lineage across pipelines, transformations, and BI tools confirmed (docs).

• Table-Level Lineage: Dataset-to-dataset lineage automatically built for connected sources (docs).

• Column-Level Lineage: Column-level lineage available — confirmed via the MCP entity_lineage tool surfacing column granularity (docs).

• End-to-End Lineage: End-to-end lineage from source ingestion through transformation to BI layer confirmed (docs).

• Impact Analysis: Upstream/downstream impact analysis exposed in the catalog and in the MCP server for automated queries (docs).

• OpenLineage Support: Not confirmed (docs).

Secoda data stewardship

Compare: data stewardship tools

• Data Stewardship: Owners (users or groups) are assigned per resource and can be set in bulk on a schedule with Automations; there is no separate steward role (docs).

• Review & Approval Workflows: Viewers request changes to any resource field, and the resource owner approves or denies the request from their inbox; single-step owner approval only (docs).

• Metadata Automation: Automations (triggers) allow rules-based metadata updates, ownership assignment, and notifications without manual intervention (docs).

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

• Governance Campaigns: Bulk governance campaigns not confirmed as a named feature beyond individual automation rules (docs).

• Governance Scorecards: Not confirmed (docs).

Secoda data classification

Compare: data classification tools

• Sensitive Data Discovery: Automated PII tagging matches column names against keywords (Premium plan) (docs).

• Native Policy Enforcement: Not yet researched — this feature was added to the taxonomy on 2026-09-21, after this tool was researched.

• Data Policy: Secoda Policies enforce metadata standards, not access to data (docs).

• Data Masking: PII columns are only hidden in in-catalog previews; no masking is applied in the warehouse (docs).

Secoda AI features

Secoda AI answers questions about your data.

• AI Features: AI assistant for natural language queries, AI-generated documentation, and automated metadata enrichment all confirmed (docs).

• AI Chat Assistant: Secoda AI answers questions about data assets using the catalog as context — accessible from the product UI (docs).

• AI Documentation Generation: AI auto-generates column, table, and schema documentation from existing metadata and usage context (docs).

• Agentic Metadata Enrichment: AI-powered automations enrich metadata at scale — classifying, tagging, and documenting assets continuously (docs).

Secoda data compliance

• Data Compliance: GDPR and HIPAA compliance frameworks confirmed — Secoda is used for compliance workflows and has SOC 2 (docs).

• Audit Trail: Comprehensive audit log of governance events, policy changes, and catalog modifications confirmed (docs).

• Compliance Reporting: Not confirmed as a dedicated compliance evidence reporting feature (docs).

• Regulatory Framework Mapping: GDPR/HIPAA compliance confirmed but explicit regulation-to-asset mapping feature not confirmed (docs).

• Data Activity Monitoring: Not confirmed — query usage tracking is in the catalog but real-time source-level activity monitoring not confirmed (docs).

• ROPA: Not confirmed as GDPR Article 30 register (docs).

• Data Retention Policies: Not confirmed (docs).

• Data Subject Rights: Not confirmed as DSAR automation (docs).

Secoda collaboration

• Collaboration: Inline comments, Slack integration, Jira integration, and team notifications confirmed (docs).

• Alert Notifications: Slack and email notifications for anomaly alerts, quality changes, and governance events confirmed (docs).

• Discussions & Annotations: Inline discussion threads on catalog assets confirmed (docs).

• Ticketing Integrations: Jira integration for creating tickets from governance tasks or quality issues confirmed (docs).

Secoda data marketplace

• Self-Service Access Requests: Access request workflows allow data consumers to request access directly from the catalog (docs).

• Data Marketplace: Not confirmed as a dedicated data marketplace (docs).

• Data Products: Not confirmed as first-class data products (docs).

• Data Mesh Support: Not confirmed as a first-class data mesh architecture (docs).

• Subscription Management: Not confirmed (docs).

Secoda data quality

• Data Quality: Data quality scores (DQS) per table, anomaly detection, and dbt test results integration all confirmed (docs).

• SQL Table Tests: dbt test results are ingested and surfaced per table in the catalog, making SQL-level tests visible in governance context (docs).

• Data Health Scores: Data Quality Score (DQS) is a per-asset composite health score surfaced in the catalog (docs).

• Anomaly Detection: Anomaly detection monitors data freshness and volume changes — alerts on unexpected deviations (docs).

• Data Profiling: Not explicitly confirmed as a dedicated profiling scan (docs).

• Data Contracts: Not confirmed as first-class data contract management (docs).

Secoda AI governance

• AI Agent Access Governance: The MCP server authenticates every agent request and enforces the user's workspace and AI permissions on it, so agents can only retrieve metadata the caller is authorized to see, with all interactions logged (docs).

• AI Governance: No AI governance product for governing AI models confirmed (docs).

• AI Asset Inventory: Not confirmed (docs).

• AI Lineage: Not confirmed (docs).

• AI Regulatory Compliance: Not confirmed (docs).

• AI Model Health Score: Not confirmed (docs).

Secoda workflows

• Workflows: Automation rules (triggers), API, Slack, Jira, and dbt integrations all confirmed (docs).

• REST / GraphQL API: REST API confirmed for programmatic access to catalog metadata (docs).

• MCP Server: Secoda MCP Server confirmed — exposes catalog search, lineage, glossary, and quality data to AI agents (docs).

• dbt Integration: Native dbt Cloud integration syncs models, tests, documentation, and column-level lineage into the catalog (docs).

• Browser Extension: Chrome extension shows Secoda context in Looker, Tableau, Snowflake, BigQuery and other tools (docs).

• Python SDK: Python SDK not confirmed (docs).

• Webhooks: Not explicitly confirmed (docs).

Secoda data context layer

• Knowledge Graph: Not explicitly confirmed as a graph architecture — Secoda's metadata model is relational (docs).

• Semantic Models: Not confirmed (docs).