How is a metric catalog different from a data catalog?
A metric catalog focuses on business-ready metrics, while a data catalog focuses on raw data assets like tables, columns, and schemas. A metric catalog abstracts complexity so business users and AI systems can rely on trusted numbers without understanding underlying data models.
Quick comparison
| Metric catalog | Data catalog | |
| Audience | Business teams, analysts, executives, AI assistants that need clear definitions and calculations | Data engineers, stewards, BI developers, analysts who manage and model raw data |
| Level of abstraction | Business concepts such as “Gross Revenue,” “Active Subscribers,” with consistent definitions, dimensions, and time grain | Technical assets such as tables, columns, schemas, lineage, owners, and policies |
| Typical use cases | Self-serve dashboards, KPI tracking, goal notifications, certified definitions for analytics and AI, consistent rollups across teams | Data discovery, impact analysis, access management, lineage tracking, schema change management, compliance and governance |
Where they complement each other
A data catalog tells you what data exists and how it flows. A metric catalog turns that data into the numbers you run the business on. They work best together.
- Source to metric link: The data catalog lists tables and owners. The metric catalog points each metric to those sources, so definitions stay traceable.
- Change awareness: Column or table changes appear in the data catalog. Metric owners see the downstream impact and update definitions before numbers drift.
- Shared vocabulary: Business terms defined once in the metric catalog map to physical assets tracked in the data catalog, which reduces rework across teams.
- Guardrails: Stewardship lives in the data catalog. Certification, naming, and descriptions live in the metric catalog. Together you get control and clarity.
Why SMBs often need metrics before metadata
Many small and mid-sized teams need outcomes fast. You may not have a full-time data engineering group or months for documentation. A metric catalog gives you usable answers while your data practice matures.
- Speed to value: You can publish shared KPIs in days. A full data catalog rollout can take much longer.
- Scarce capacity: When one person wears many hats, a curated set of certified metrics beats a large inventory of undocumented tables.
- Consistency beats completeness: Leadership needs the same answer every time for “MRR,” “CAC,” and “Churn.” A metric catalog enforces that.
- Lower cognitive load: Non-technical users search for a metric, not for table names or join keys. That keeps adoption high.
- AI readiness: Copilots do better with a clear metric layer. Short, unambiguous definitions and calculation rules reduce hallucinations and mistakes.
- Right-sized governance: You can start with key metrics today and add deeper metadata controls as your stack grows.
Quick scenarios
- Marketing: You want “Paid CAC” by channel this quarter. The metric catalog stores the formula, filters, and time grain. Under the hood, the data catalog tracks which ad platform tables feed it.
- Finance: You report “Net Revenue” monthly. The metric catalog defines exclusions and adjustments. The data catalog documents the ledger tables and ownership.
- Customer success: You watch “Active Accounts” and “Logo Churn.” The metric catalog standardizes activity thresholds. The data catalog maps the event streams and pipelines.
Risks and considerations
A metric catalog is not a substitute for data quality. It depends on clear links to vetted sources.
- Garbage in, garbage out: Poor data quality will still surface as poor metrics. Monitor freshness and completeness.
- Naming collisions: Lock down naming rules so “Revenue” and “Gross Revenue” do not compete.
- False precision: Document rounding, currency, and time grain. Make intent obvious to avoid misleading comparisons.
- Ownership model: Assign metric owners and reviewers. Align this with the owners listed in the data catalog.
Where PowerMetrics fits
PowerMetrics provides a centralized metric catalog designed for SMB teams that need trusted numbers without heavy data engineering.
- Create governed, reusable metrics with names, descriptions, formulas, dimensions, and time grains.
- Tag, certify, and assign owners so teams know which metrics to trust.
- Connect to spreadsheets, services, databases, and warehouses, then link metrics to the underlying sources.
- Build and share dashboards from the same metric definitions, so every view matches.
- Use PowerMetrics AI to ask questions in plain language backed by the metric catalog.