Ingestion → Modeling → Analytics

Helping businesses create space to grow through better data.

I connect the systems you already run, model the data so every number means one thing, and turn it into dashboards — and AI you can actually ask questions of. One person, start to finish.

Schedule a Free Consultation See how it works

The animation shows business systems such as QuickBooks, a CRM, point of sale and payroll feeding into a lakehouse, where data is modeled into a sales fact table with customer, product, date, sales rep, location and channel dimensions, then published through a semantic layer to Power BI reporting and an AI assistant connected by an MCP server.

How it works

One engineer for the whole path.

Most projects stall at a handoff — the person who moves the data isn't the person who models it, and neither of them builds the report. I do all three, so nothing gets lost in translation.

1

Ingestion

Connect the systems you already run — accounting, CRM, point of sale, payroll, spreadsheets — and land the data somewhere central on a schedule. No more exporting by hand.

PythonREST & API integrationsAzure Data Lake Gen2Scheduled refresh
2

Modeling

Shape raw records into a star schema with a semantic layer on top: one definition per metric, relationships that hold up, history you can query. This is the part that makes everything downstream trustworthy.

Star schemaSynapse Serverless SQLSemantic layerDAX
3

Analytics

Where the value actually lands. Dashboards for the numbers you watch every week, and AI you can ask the questions a dashboard never anticipated — both reading from the same governed model.

Power BIMCP serversCertified metricsExecutive reporting
Analytics

Analytics is the deliverable. Three ways it gets built.

Ingestion and modeling are the foundation — worth doing well, but nobody buys a foundation. These are the things you actually use. Start anywhere on the list; each one builds on the last.

Reporting

Dashboard development

Power BI reports built on the modeled layer, so every number traces back to one definition. They refresh on a schedule and are built to hand off — nobody rebuilds them by hand each month.

  • Executive and operational views
  • KPIs with agreed definitions
  • Scheduled refresh, no manual exports
  • Built to be handed off and maintained
Exploration

Conversational analysis with MCP

An MCP server connects an AI assistant straight to your data model, so you can ask questions in plain language and get answers grounded in your actual records — not a guess from a chatbot.

  • Ask follow-up questions no report anticipated
  • Answers cite the underlying data
  • Works alongside your existing dashboards
  • Useful for one-off analysis without a ticket
Governed

A curated AI layer

A finished layer built for AI to read: certified metrics, business definitions and guardrails above the model. The assistant answers from the same logic as your reports, so the number in chat matches the dashboard.

  • Certified metrics with clear ownership
  • Consistent answers across people and tools
  • Guardrails on what AI can reach
  • Ready for wider rollout across a team
Services

Practical analytics support for growing businesses.

01

Dashboard Development

Interactive Power BI dashboards that give you instant visibility into the metrics that matter most.

02

Reporting Automation

Eliminate repetitive reporting by automating data collection, transformation, and visualization.

03

Business Intelligence

Turn your business data into decisions with meaningful KPIs and executive reporting.

04

SQL & Data Management

Organize and optimize your data so reporting is accurate, reliable, and scalable.

05

Data Ingestion & Pipelines

Get data out of the systems you already use and into one place, on a schedule, without manual exports.

06

AI & MCP Integration

Connect an AI assistant to your data model so your team can ask questions and get answers they can trust.

Why work with me

Technology should simplify your business, not complicate it.

I work directly with business owners and teams to understand how they operate before building solutions that actually solve problems.

  • Simple to understand
  • Easy to maintain
  • Built for real business decisions
  • Designed to save time
Experience

Analytics engineering with a business-first approach.

I've worked with organizations across multiple industries to improve reporting, streamline workflows, and help teams make better decisions with their data.

Power BI SQL Python Microsoft Fabric Azure Data Lake Synapse Data Modeling Star Schema Semantic Layers MCP Servers Dashboard Design Process Automation
Process

How a project comes together.

01

Discover

Learn your business and understand your reporting challenges.

02

Design

Create dashboards and reporting solutions tailored to your goals.

03

Deliver

Launch a solution that's easy to use and built to grow with your business.

Portfolio

Featured project: retail analytics, end to end.

Luma Retail executive dashboard built in Power BI, showing revenue to budget, top product sales, international revenue by country, and revenue by category

Luma Retail — Sales & Revenue Dashboard

Data pipeline · Data model · Power BI report

A complete analytics solution built from raw transaction data. A Python script ingests and cleans real retail invoice data, lands it in Azure Data Lake Storage, and Synapse serverless SQL shapes it into a star schema — powering a Power BI dashboard that tracks revenue against budget, top products, international sales, and category performance.

Python Azure Data Lake Gen2 Synapse Serverless SQL Star Schema Power BI
Architecture diagram: UCI Online Retail dataset ingested by a Python script into Azure Data Lake Storage Gen2, modeled with Synapse serverless SQL into a star schema, and reported in Power BI
Pipeline architecture — from raw data to report.
Power BI model view showing a star schema: f_transactions fact table related to d_date, d_customers, d_products, and d_country dimension tables
Star schema model — one fact table, four dimensions.

Ready to spend less time managing reports?

Whether you're looking to build your first dashboard or improve an existing reporting process, I'd love to hear about your business.

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