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A right-sized data warehouse — without buying complexity for nothing.

I structure your cloud data warehouse with the same layered, governed method, on the platform that fits your volume and budget: Snowflake, BigQuery, PostgreSQL or SQL Server. The choice comes from the problem, not the trend.

A human reply · a diagnostic before any build · mutual NDA

01The problem

Recognize any of these symptoms?

Data scattered across ERP, database, spreadsheet and legacy system.
Every analysis starts with a hunt for the data before any insight.
Fear of picking the wrong platform and paying dearly for it.
02What's included
  • Platform choice based on your case, not on hype
  • Layers (staging, marts) and governance
  • Centralizing the sources into one reliable place
  • Cost control and documentation
03How it works
  1. 1

    Diagnostic

    I understand volume, sources, budget and who will consume the data.

  2. 2

    Platform choice

    I recommend the right option — and tell you when you don't need the most expensive one.

  3. 3

    Layered modeling

    I organize staging and marts so the data becomes reliable and reusable.

  4. 4

    Governance

    Documentation, access control and cost control to scale without surprises.

04Frequently asked questions

Common questions about cloud & data warehouse.

Which platform do you recommend?

It depends on the case. For many SMB scenarios, PostgreSQL or BigQuery solve it at low cost. Snowflake shines at higher volume and concurrency. I recommend by need, with honesty about where I have the most direct experience.

Is it worth migrating now?

Not always. Sometimes the gain is in organizing what exists before migrating. In the diagnostic I tell you whether the migration is worth it.

What about cloud cost?

Cost control is part of the design — modeling and scheduling thought out so the bill doesn't blow up at month-end.

Want me to look at your case?

A 30-minute call, no commitment. I'll tell you where the risks are and what to fix first.