Metric Catalog
A metric catalog is a centralized library of standardized metrics and KPIs, each with a clear name, formula and description. Think of it as a reference guide that ensures everyone in your organisation measures success the same way.
In depth
A metric catalog goes beyond a simple list of numbers. It serves as the single source of truth for how your business defines and calculates performance indicators. Each entry in the catalog typically includes:
Metric name: A concise, descriptive title.
Definition: A natural-language description explaining why the metric matters.
Formula or calculation: The exact steps or SQL query used to derive the value.
Data source: The raw tables, files or services the metric draws from.
Metadata: Tags, owner, certification status and refresh schedule.
By maintaining this structured information, teams can avoid confusion caused by duplicated or inconsistent metric definitions. Data analysts gain confidence that they’re working with the right logic while business users trust the numbers they see in reports and dashboards.
Modern metric catalogs often integrate with a semantic layer or metric platform, enabling self-serve analytics without sacrificing governance. In an AI-ready setup, a catalog might power natural-language queries, automatic lineage tracking and error propagation.
Pro tip
Use consistent naming conventions and add tags for departments, data owners and business goals. This makes it easy for users to search and filter metrics when building dashboards.
Why it matters
Without a metric catalog, teams risk inconsistent reporting, wasted time reconciling different versions of the same KPI and reduced trust in data. A solid catalog fosters:
Data confidence: Everyone works from the same definitions.
Faster insights: Users find and reuse metrics instead of reinventing the wheel.
Better governance: Data teams retain control while empowering business users.
Metric Catalog - In practice
Imagine your marketing and finance teams both track “monthly recurring revenue (MRR)”. Without a catalog, marketing might calculate MRR based on subscription orders, while finance uses billing dates.
A metric catalog ensures both teams reference the same MRR definition, sourced from a central data warehouse, certified by the analytics team and available in self-serve dashboards. That alignment speeds up monthly reports and helps leaders make confident decisions.
Product-specific notes
In Klipfolio PowerMetrics, the curated metric catalog is built-in. Users can:
Browse 100+ instant metrics with descriptions at MetricHQ.
In PowerMetrics, make use of the metric certification status and tags.
Allow users to create DIY dashboards using trusted, standardised metrics from the catalog.
Leverage PowerMetrics AI to ask questions in natural language and get metric-driven answers.
Related terms
Key Performance Indicator (KPI)
A key performance indicator (KPI) is a measurable value that shows how effectively your organization is achieving its most important objectives. Think of a KPI like a car’s speedometer—each gauge gives you real-time feedback so you can adjust your course and hit your destination.
Read moreData Governance
Data governance is the system of people, policies, and tools that keeps data accurate, secure, and usable across your company. Think of it like hiring a skilled librarian for a massive library. Every book is cataloged, protected, and easy to find, so readers trust what they pick up and can act quickly. With solid governance, your team works from the same definitions, follows clear rules for access and use, and treats data as a business asset.
Read moreKnowledge Graph
A knowledge graph is a structured network that represents real-world entities (people, places, products, metrics) and the relationships between them. It adds context and meaning to data, so systems and people can make smarter, more reliable decisions rather than just matching keywords or numbers.
Read moreMeasure
A measure, in the context of data, is a quantifiable numeric value used to track and analyze data. It represents a calculation—like sum, average or count—that you perform on raw data points.
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