Your board asks a question.
You can't answer it.
I help companies where analytics is blocking something important: a fundraise, a launch, keeping critical hires, or building team trust in the numbers. Ex-Meta engineer. Fixed-scope diagnostics in 10 business days. You get a roadmap, not a sales pitch, so you can move forward with confidence.
No prep needed. NDA available. If I am not the right fit, I will tell you.
Problems We Solve
If any of these sound familiar, I can help.
"Your first data hire is drowning and might quit"
You hired someone to fix analytics. Three months later they're firefighting pipelines, fielding ad-hoc requests, and haven't shipped the dashboard you actually need. You're wondering if you hired wrong. You didn't. They're underwater because there's no foundation.
- •They rebuilt the same query five times because there's no semantic layer
- •They can't onboard because nothing is documented
- •They're Slacking you at 9pm because a pipeline broke again
"Sales and finance report different revenue numbers"
Every week, someone asks "what's our MRR?" and gets three answers. Sales pulls from Salesforce. Finance pulls from Stripe. Product pulls from your warehouse. You're spending more time reconciling numbers than using them. The problem isn't the tools. It's that nobody defined what "revenue" means.
- •Board meetings start with 15 minutes of "why don't these match?"
- •Leadership stopped trusting dashboards and went back to spreadsheets
- •Your data person fields more "which number is right?" than actual analysis
"You're about to raise and your metrics are a mess"
Investors want a data room. You have Looker dashboards, a Snowflake warehouse, and five different ways people calculate retention. Your fundraise timeline just got longer because you need two weeks to get your numbers straight. Or you present messy data and investors assume operational chaos.
- •User counts vary by 20% depending on who you ask
- •You can't produce a clean cohort analysis without three days of work
- •Your CFO is rebuilding the data room in Excel because they don't trust your BI tool
Executive Analytics Readiness Checklist
How ready is your analytics infrastructure?
If you answered "no" to 3+ items, the full checklist will help you pinpoint the highest-ROI fixes.
Free • No spam • 26-point comprehensive guide
How We Help
Four ways I help. If you are not sure where to start, start with the audit.
Analytics Infrastructure Audits
10 business days
Find out why your analytics feels broken in 10 business days. You get: what's actually wrong, what it's costing you, and the smallest fix that unblocks progress. Fixed scope, written deliverables, no upsell.
Learn more →Metric Governance & Semantic Layers
~3–6 weeks
Stop the weekly "which number is right?" meeting. Define your top 10 metrics once, with edge cases and ownership, so sales and finance finally agree. Your data team stops rebuilding the same logic in every dashboard.
Learn more →Pipeline Development & Optimization
~4–8 weeks
Stop waking up to broken pipelines. Build or fix your data flows so they recover automatically, alert before they're critical, and don't balloon your warehouse bill. Your data hire stops firefighting and starts shipping.
Learn more →BI Platform Setup & Dashboarding
~3–6 weeks
Build dashboards people actually check. Fast enough to not be annoying. Clear enough to drive decisions. Tied to your semantic layer so the numbers don't drift. Your leadership stops asking for spreadsheet exports.
Learn more →Proof without the logo wall
New consulting practice. Not new to analytics systems. Here is what you can expect, in plain English.
Fixed-scope audit deliverables
The audit is designed to be a clean starting line. Clear scope. Clear outputs. No vague "assessment" vibes.
- •A simple data flow diagram you can hand to a new hire
- •A list of reliability and data quality risks (ranked by severity)
- •A metrics trust review: where definitions drift and why
- •A prioritized roadmap with effort levels and dependencies
Process clarity
You always know what I am doing, what you are getting, and what happens next.
- •Audit: find the bottlenecks and trust gaps
- •Roadmap: define the smallest set of fixes that unlock progress
- •Implementation: ship production-ready changes (code, tests, docs)
- •Enablement: handoff, training, and runbooks
Clear boundaries (so you know what you're buying)
Consulting should not feel like buying hope. You should know what you're getting before you pay.
- •The audit is a fixed deliverable: data flow map, severity-ranked issues, prioritized roadmap with effort levels
- •Implementation has clear milestones you can point to ("metric definitions documented and in code")
- •Weekly written updates you can forward to your boss or board
- •Handoff includes runbooks and walkthroughs, not "good luck"
How Engagements Work
A clear process from first call to handoff.
Discover
Free 20-min call to understand your pain points, stack, and goals.
Audit
Quick diagnostic (1–2 weeks) to assess what's broken and prioritize fixes.
Roadmap
Deliver a clear plan with timelines, milestones, and deliverables.
Implement
Build and deploy: pipelines, metrics, dashboards, or governance frameworks.
Enablement
Train your team and hand off documentation so you're self-sufficient.
Why "Actually"?
Too many analytics projects deliver dashboards that look good but don't get used. Metrics that sound official but aren't trusted. Infrastructure that's "best practice" but doesn't fit your reality.
I focus on what actually matters: clarity, trust, and speed. Metrics you can bet decisions on. Dashboards people check daily. Pipelines that just work.
I spent years building measurement and analytics infrastructure at Meta. Now I bring that same rigor to companies that need it fixed fast, sized for your reality. You get dashboards people actually check, metrics you can bet decisions on, and pipelines that just work.
Common Questions
Do we need to use specific tools?▼
Nope. I work with your stack, whether that's Snowflake or Postgres, dbt or custom SQL, Looker or Metabase.
Can we do this internally?▼
Maybe! If you have experienced analytics engineers, yes. If your first data hire is drowning or you're stuck, outside help accelerates.
How long does it take?▼
Audits: 1–2 weeks. Implementation: 3–8+ weeks depending on scope. We set clear milestones upfront.
Want your numbers to stop being a debate?
Request a free 20-minute fit call. Or grab the checklist and audit your setup in 15 minutes.