Most large data estates define revenue more than once. There's a version in the Power BI semantic models, another in the Tableau data sources, an older one in a MicroStrategy project, and since last year, one more in a Snowflake semantic view someone built for an AI pilot. Each was built correctly, by a different team, in a different tool.
That holds until the CFO's deck and the sales dashboard show different numbers in the same meeting. Three gaps decide whether your team settles it in an hour or loses the sprint to it:
- Duplication. Every BI tool keeps its own copy of the metric, so every new report, tool, or AI interface adds another copy to keep aligned.
- Divergence. Two copies can share a name and differ by one filter or one join. Finding which one takes days of side-by-side screenshots, because neither tool knows the other exists.
- Rebuild. A BI consolidation moves the reports and leaves the definitions behind, so someone re-types years of calculations in the new tool's dialect, under deadline.
What changes with MetaKarta
The divergence on screen, expression and all. MetaKarta traces both versions of the metric back through the BI models, the ETL, and the SQL to their source columns, at column level. The filter or join that separates the two numbers shows up with its expression visible.
Import what you already run. MetaKarta reverse-engineers existing semantic models from Power BI and Tableau, legacy BI tools like MicroStrategy, SAP BusinessObjects, IBM Cognos, and Oracle OBIEE, and databases like Snowflake, Databricks, Oracle, and SAP HANA. Years of joins, hierarchies, and metric logic become a governed starting point instead of a rebuild.
Settle each conflict once. When two imports define the same metric differently, both expressions stay visible side by side, and the owner of the definition picks the canonical one. Data Governance records who made the decision and when.
One definition, compiled into every tool. Semantic Hub compiles the governed definition into native Snowflake Semantic Views, Databricks Metric Views, Oracle Analytic Views, Power BI semantic models, Tableau logical models, and LookML. We don't sit in your query path. We've already compiled into your database and tools.
How it works
MetaKarta runs on one shared metadata repository, so the trace, the definition, the steward's decision, and the compiled artifact all describe the same metric.
- Semantic model import: Existing BI and database semantic models reverse-engineered into a governed catalog, with role-playing dimensions resolved and inferred joins flagged for review
- Reconciliation: Conflicting definitions of one metric kept side by side, with a YAML diff, until a steward chooses
- Expression conversion: Calculations converted between database and BI dialects, with validation flagging anything that won't run in a target
- Test before deploy: The governed model run against live data, with the generated SQL visible, before any user sees a number
- Native compilation: One model deployed as each target platform's own artifact, with nothing added to the query path
- Column-level lineage: Every compiled metric traced back to its source columns across 400+ native connectors
See it on your own estate
Three checks make a useful evaluation of any approach to metric consistency, including ours:
- The two-versions check. Pick a metric two dashboards disagree on. Ask for both definitions on one screen, with the filter or join that separates them, without anyone exporting a screenshot.
- The oldest-model check. Pick a semantic model from the BI tool you'd most like to retire. Ask to see it imported with its calculations intact, then deployed to the tool replacing it.
- The one-change check. Change a governed definition once. Then count the tools, warehouses, and agents that pick up the change without anyone re-typing it.
Built on nearly 30 years of metadata engineering
MetaKarta's metadata technology runs inside the products of Microsoft Purview, Informatica from Salesforce, IBM, Oracle, and Qlik Talend. MetaKarta brings that engine to your estate directly, with definitions that stay portable as native artifacts in the tools you already own.
When revenue is defined once and compiled into every tool, the reconciliation meeting turns into a lookup. The number to watch is how many of your top metrics return the same value in every tool that computes them.
Get in touch to learn more about how MetaKarta compiles one governed revenue definition into every BI tool you run.
