03 THE MULTIPLIER

Version-controlled, governed business logic.

I untangle messy JSON and raw tables into clean, version-controlled dbt models and DAX semantic layers, ensuring your data is standardized, tested, and ready for BI consumption.

Standardize Your Metrics
The Bottleneck

The Cost of Raw Data

01

You are suffering from sprawling logic. When analysts write heavy SQL queries directly inside BI tools, calculations become untrackable. If a formula changes, you have to manually update 50 different dashboards.

02

Your dashboards are timing out. Forcing a visualization tool like Power BI to parse unstructured JSON or massive flattened audit trails causes the engine to crash, leaving executives staring at loading screens.

03

Your data has zero quality assurance. Without automated dbt tests running upstream, bad data feeds directly into your reports, eroding trust in the analytics entirely.

Semantic Layer Architecture

RAW WAREHOUSE DATA
UNTYPED JSON / MESSY TABLES
↓
THE SEMANTIC LAYER
KIMBALL STAR-SCHEMAS VERSION-CONTROLLED SQL AUTOMATED DATA TESTS

DBT ยท DAX MODELS

↓
CERTIFIED OUTPUTS
BI DASHBOARDS
METRIC CATALOGS
02 THE ENGAGEMENT

Scope & Deliverables

Every semantic engagement is scoped strictly to your operational reality. No bloat. No guesswork.

01

DAX & Power BI Models

  • 2-4 Weeks Delivery Timeline
  • SSAS Tabular Model Development
  • Complex DAX Measure Engineering
  • Dynamic Currency (FX) Conversions
  • Row-Level Security (RLS) Implementation
Ideal For

Organizations deeply embedded in the Microsoft stack that need to optimize their Power BI reporting layer for massive datasets.

Most Common Scope 02

dbt Semantic Layer Rollout

  • 4-8 Weeks Delivery Timeline
  • Kimball Dimensional Modeling (Star Schemas)
  • Version-Controlled SQL via Git
  • Automated Data Testing & Assertions
  • Auto-Generated Metric Documentation
Ideal For

Modern data teams scaling rapidly on Snowflake or Databricks who need strict engineering governance applied to their business logic.

Post-Deployment

Operations & Maintenance

Data systems decay without active maintenance. My O&M retainers keep your semantic infrastructure secure, optimized, and evolving as your business definitions change.

01

Metric logic updates & iteration

02

Automated test monitoring

03

Performance & query optimization

04

Git repository management

Frequently Asked Questions

Why do we need dbt if we already write SQL? +
Writing loose SQL scripts directly into reporting tools makes your logic impossible to track. dbt introduces software engineering best practices to data. It allows you to version-control your logic in Git, automatically test for bad data before it hits the dashboard, and modularize your code so you only have to update a metric formula in one single place.
Do we need a semantic layer if we only use Power BI? +
If your organization exclusively uses Power BI, we can build a highly optimized semantic layer using DAX and SSAS. However, if your data teams use a mix of tools (e.g., Power BI for executives, Python for data science, and Excel for finance), a central dbt semantic layer sitting in Snowflake/Databricks ensures all of those distinct tools report the exact same numbers.
Do you maintain the code after handover? +
Yes. After the initial build, I offer dedicated B2B fractional retainers. This ensures your infrastructure is actively monitored, new metrics are added cleanly, and your internal team receives ongoing architectural enablement.

What Happens Next?

Your operational data is now structured, tested, and certified in the semantic layer. The final move is feeding this unshakeable data into interactive dashboards so leadership has real-time KPI visibility.

Explore BI Dashboards →