Data Platform Assessment
A target architecture and migration sequence for your data estate, from spreadsheet sprawl or aging warehouse to something your team can run.
What you get
- Current-state data estate mapSources, pipelines, reports, and the undocumented Excel steps in between, drawn as they actually are.
- Pain map tied to business costWhere reporting is slow, duplicated, or hand-assembled, and what each pain costs in hours and decisions.
- A target architectureWarehouse, lakehouse, or a well-organized Postgres, chosen for your workloads and your team, not for a logo slide.
- Platform comparison for your caseSnowflake, Databricks, Fabric, and open-source paths compared on cost, skills required, and fit. We hold no vendor partnerships to defend.
- A migration sequence with a cost modelWhat moves first, what retires, and what the phases cost, so the project can start small and prove itself.
What we need from you
- Interviews with the people who build and consume the reports (about three hours).
- Read-only access to, or schema exports from, the main data sources.
- The three reports leadership actually reads, so the target design starts from them.
Timeline
Interviews and estate mapping.
Target architecture, platform comparison, and cost modeling.
Migration sequencing, written report, and walkthrough (smaller estates finish in two weeks).
Who it's for, and who it isn't
- Reporting depends on a person, not a platform.
- The current warehouse predates half the systems feeding it.
- AI plans keep stalling on "our data is a mess."
- You have a data team mid-migration already. This would second-guess them; bring us in only if you want that.
- One dashboard would solve it. We will tell you that on the scope call and point you at cheaper help.
Sample deliverable: table of contents
- 1 · Executive summary
- 2 · Current-state estate map
- 3 · Pain map and business cost
- 4 · Target architecture
- 5 · Platform comparison
- 6 · Migration sequence and phased cost model
Common questions
Do you resell any of the platforms you compare?
No. We hold no data-platform partnerships, which is unusual in this market and worth asking every other firm about. Snowflake, Databricks, Fabric, and open-source paths get compared on your workloads, your team, and your budget.
Our data is mostly spreadsheets. Is this premature?
No, that is the most common starting point we see, and it is the cheapest moment to design the platform right. The report meets the estate where it is.
Do you factor in our team’s skills?
Heavily. A technically superior platform your team cannot operate is a worse choice than a good-enough one they can, and the comparison scores operability alongside capability and cost.
Can you execute the migration afterward?
Yes, as a follow-on project, and the sequence is deliberately designed to start small and prove itself before anything big moves. The assessment stands alone if you execute with someone else.
Related
Connect with us about your data estate.
Bring the report that takes someone two days a month to assemble. That is usually where the design starts.