Fractional Data Architect on Thomas Nys | Fractional Data Architect

Your data platform has 15 incidents per month.

This company piloted Data Mesh with 2 domains in 6 months.

Your data testing pyramid is upside down.

Your architecture decision has been stuck for 8 weeks.

AI is generating data quality tests now.

An executive requested a simple revenue dashboard.

You test your code.

Nobody budgets for technical debt.

Every governance rebuild I’ve seen starts the same way: a team that over-corrected once, then over-corrected the other way, and is now tired of both.

“Do nothing” is never free.

Treating finance and customer analytics like the same workload is how you end up with a platform that serves neither well.

Your data pipelines run in production.

Six months ago our senior engineers were firefighters.

Most maturity assessments take six weeks and a consulting firm.

Executives stopped using the dashboards.

Your custom Airflow setup is not a competitive advantage.

You don’t migrate a data platform in one go.

Your data team switches between four tools during an incident.

The data contract didn’t save the launch.

Everyone agrees on “data ownership.”

Two full-time equivalents on your data team do nothing but answer questions all day.

This company was burning six figures a year on cloud data - we cut it by 45% in 8 weeks.

Without data lineage, every schema change is a game of “what did we just break.”

Your data roadmap is a wishlist - here’s the 3-horizon framework that turns it into strategy.

The unicorn data engineer doesn’t exist - but the balanced data team does.

When the CFO opens Excel instead of your dashboard, your data team has already lost.

Your engineers want to build it, your CFO wants to buy it - here’s the framework that settles it in 30 minutes.

The 2x2 matrix isn’t new - but most data teams still score “value” completely wrong.

A client budgeted for a full-time data architect they couldn’t find, so we tried something different. 80-person company.

Your data governance is either too loose to trust or too tight to ship.

If every alert is critical, none of them are.

90% of “we need real-time” conversations end with a batch job running at midnight.

A data team spent 60% of their week doing the same manual tasks - and nobody questioned it for two years.

The best data strategy I’ve seen fit on a single page.

The DevOps playbook assumes you can roll back - data doesn’t work that way.

Data contracts sound great in theory.

Bronze, Silver, Gold.

Hot, warm, cold.

Your data team hides problems because they’ll get blamed for them.

The most expensive way to avoid fixing your organizational problems: migrate to a new data platform.

When your data breaks, how long until someone notices?

Your data platform is burning money in three places right now.

Due diligence found 15 “temporary” integrations from 2019 still running in production.

Every data team has a Brent.

“Self-service analytics” at most companies means “we gave everyone PowerBI access and hoped for the best.”

Stop hiring full-stack data engineers.

Three months of development.

You can’t fix what you can’t trace.

Your data team deploys to production the same way software teams did in 2008.

Due diligence will find your data problems before you do.