Data Strategy & Business Intelligence
Get to one set of numbers everyone believes.
Most companies have the data. It's just in six places that disagree. Sales says one revenue number, finance says another, and the meeting turns into an argument about whose export is right instead of what to do next.
A data strategy is just deciding, on purpose, where each number comes from and who owns it. I map what you have now, build the plumbing that pulls it into one place, and put the handful of dashboards on top that people will actually open. Then we agree which number is the real one.
Key outcomes
One set of numbers
One place the numbers come from, and one definition of each one.
Real-time visibility
You can see today's numbers today, not on the fifth of next month.
Make data-driven decisions
Arguments end faster when everyone is reading the same chart. Judgment still matters. It just starts from facts.
Service offerings
Three steps, in order: find out what you actually have, build the pipes, then put dashboards on the end. Skipping the first step is why most BI projects die.
Data and systems audit
I inventory every system that holds a number, every place two of them overlap, and every spot where a person retypes something.
Architecture design
I design the middle: where the data lands, how it's shaped, and how it grows without a rewrite in two years.
Pipelines and integration
I build the jobs that pull from your CRM, your ad accounts, and your support desk on a schedule, so nobody exports a CSV again.
Dashboards and reporting
Looker Studio, Tableau, or something custom if those don't fit. Few dashboards, well chosen, is better than forty nobody opens.
Results
You get to ask a question on Tuesday and have the answer on Tuesday. Which campaigns paid for themselves. Where the support load actually comes from. Which customers went quiet last month. And the meeting stops being about whose spreadsheet is right.