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What is Secoda?

Secoda is a data intelligence platform that brings cataloguing, lineage, observability and governance together in one place. It connects to data warehouses, BI tools and transformation layers to centralise metadata, document assets and track quality. Secoda AI lets teams search and ask questions about their data in natural language, drawing on context across the connected stack. It is aimed at data teams and enterprises that need to manage discovery, access and compliance at scale.

Key Features

Data catalogue and search

Centralised repository of data assets with AI-assisted discovery across connected sources.

Column and table-level lineage

End-to-end visualisation of how data flows and where it originates.

Secoda AI

Natural-language search and analysis that answers questions using context from the connected stack.

Data monitoring and quality

Observability with a Data Quality Score and alerts on issues.

Governance and access control

Role-based access control, policies, PII scanning and SAML support.

Automations and API

Workflow automation, bulk metadata operations and API access for custom integrations.

Integrations

Connectors for warehouses and BI tools including Snowflake, BigQuery, Databricks, dbt, Tableau and Looker.

Pros & Cons

Advantages

  • Brings cataloguing, lineage, monitoring and governance into a single platform rather than separate tools.
  • Secoda AI allows natural-language search across the data stack, lowering the barrier for non-technical users.
  • Wide range of connectors covering common warehouses, BI and transformation tools.
  • Strong security and deployment options including SAML, RBAC, single-tenant and self-hosted setups.
  • Automation and API access support bulk metadata work and custom workflows.

Limitations

  • No public pricing is listed, so all plans require contacting sales for a quote.
  • There is no free plan and no advertised free trial on the pricing page.
  • Some governance features such as policies, PII scanning and single-tenant deployment are reserved for higher tiers.
  • The breadth of features may be more than smaller teams with simple data setups need.

Use Cases

Data engineers use it to map column and table-level lineage and trace the impact of upstream changes.

Data analysts and business teams search and ask questions about data assets using Secoda AI.

Governance managers enforce policies, role-based access and PII scanning for compliance.

Data teams monitor quality with the Data Quality Score and act on alerts before issues spread.

Organisations centralise documentation and metadata to onboard new team members faster.

Enterprises with sensitive data deploy self-hosted or single-tenant instances with SIEM logging and custom roles.