Select Star
Active metadata management software
Machine learning data catalog software
Data governance tools
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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- Information technology and software
- Banking and insurance
- Retail and wholesale
What is Select Star
Select Star is a data discovery and governance platform that provides a data catalog, lineage, and documentation across analytics and data engineering assets. It targets data teams that need to understand datasets, dashboards, and pipelines, and to standardize definitions and ownership for governed self-service analytics. The product emphasizes automated metadata collection from connected systems and uses metadata signals to recommend documentation and relationships between assets. It is typically used for dataset discovery, impact analysis, and improving trust in analytics outputs.
Automated metadata harvesting
Select Star connects to common data warehouses, BI tools, and orchestration systems to ingest technical metadata with limited manual effort. This supports faster catalog population than approaches that rely heavily on manual curation. Automated refresh helps keep asset inventories current as schemas and dashboards change. This is useful for organizations with rapidly evolving analytics environments.
Lineage and impact analysis
The product focuses on mapping relationships between upstream sources, transformations, and downstream tables and dashboards. This helps teams assess the blast radius of schema changes and troubleshoot data quality issues. Lineage views also support governance workflows by clarifying accountability and dependencies. These capabilities align with common requirements in modern data stacks.
Documentation and ownership workflows
Select Star supports capturing business context such as descriptions, owners, and tags on data assets. This helps standardize definitions and reduce duplicated or inconsistent metrics across teams. Workflow features can be used to drive completion of documentation and stewardship tasks. These functions are central to operationalizing governance beyond a static catalog.
Integration coverage varies
The usefulness of automated cataloging depends on the breadth and depth of supported connectors for a given environment. Some organizations may require custom integrations for niche databases, legacy systems, or specialized BI tools. Where connectors are limited, teams may need manual metadata entry or engineering effort to close gaps. This can slow time-to-value for heterogeneous stacks.
Governance depth may be limited
Organizations with complex governance programs may need advanced capabilities such as fine-grained policy management, regulatory mapping, or extensive workflow customization. If those needs exceed the product’s native features, teams may need complementary tooling or additional process controls. This is a common consideration when comparing catalog-led governance approaches. Fit depends on the maturity and compliance requirements of the organization.
Adoption requires process change
A catalog and governance layer delivers value only when teams consistently document assets and use the system in daily work. Without clear ownership, incentives, and operating procedures, metadata can become stale even with automated ingestion. Rollout often requires training and alignment across data engineering, analytics, and business stakeholders. This organizational effort can be non-trivial.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Custom / Contact Sales | Not published — contact sales | Flexible pricing tailored to customer needs; pricing counts data sources by type (multiple connections to same source type count as one); subscription-based (fees set forth on Select Star fee schedule); 12-month automatic renewal typical per MSA; 14-day free trial available. |
Seller details
Select Star, Inc.
