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Data modeling, DAX, and SQL that make your numbers agree

When finance, operations, and sales each have a different number for the same thing, the problem is usually the model underneath. We fix the logic so every report draws from one definition.

Comic book style illustration: Analyst working at a desk with two monitors

Signs your data model needs work

Dashboards are only as trustworthy as the logic behind them. These are the symptoms we see most often.

Data model diagram showing related tables

What we deliver

Clean structure underneath means faster reports and fewer arguments on top.

Data models

Star-schema models that make reports fast and calculations predictable.

DAX measure libraries

Reusable, documented measures for margin, utilization, growth, and more.

SQL views and logic

Business rules written once in the database instead of copied into every report.

Metric definitions

A plain-language glossary of what each number means and where it comes from.

Performance tuning

Faster refreshes and visuals through model, query, and storage improvements.

Validation checks

Tests that compare report totals against accounting so errors surface early.

How we approach it

1

Trace and reconcile

We find where numbers diverge and why, down to the specific rule or join.

2

Design the model

We lay out tables, relationships, and definitions and review them with you.

3

Rebuild and validate

We rebuild the logic and check results against your source systems.

4

Document definitions

Every metric gets written down so the next person can maintain it.

Common questions

Have a different question? Ask us directly.

Yes. Many projects start by fixing an existing Power BI or Tableau model rather than replacing it.

SQL Server, Azure SQL, Google BigQuery, PostgreSQL, and MySQL, plus Excel and Google Sheets when that’s where data lives.

Often yes. Fixing the definitions early prevents every future report from inheriting the same problems.

Related services

Dashboards built around the decisions your team makes every week.

Automated data movement into one central, historical warehouse.

So your team can read, use, and maintain its own reporting.

Start with a data audit

We’ll review your systems and current reports. You’ll leave with a clear plan for what to build first, whether we build it or not.