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Building a Data Platform Incrementally Print

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Growing capability sensibly.

WHAT TO BUILD FIRST

One pipeline, from one source, producing one report someone uses.

WHY

It proves value and reveals the real obstacles.

WHAT TO RESIST

Selecting a full tool stack before the first use case.

WHAT THE SENSIBLE PROGRESSION IS

A database and scheduled scripts A warehouse and a transformation framework An orchestrator, when dependencies justify it Quality testing, as trust becomes important Cataloguing and governance, as consumers multiply Streaming, only where latency demands it

WHAT TO ADD EACH TIME

What the current pain requires.

WHAT PAIN INDICATES WHAT

  • Manual steps repeated: automation
  • Numbers disputed: definitions and testing
  • Nobody knowing what exists: cataloguing
  • Pipelines breaking silently: monitoring
  • Cost surprising: attribution and limits

WHAT TO AVOID

Infrastructure requiring more operation than the organisation can sustain.

WHY THAT MATTERS PARTICULARLY WITH SMALL TEAMS

An elaborate platform operated by nobody degrades into an unreliable one.

WHAT TO MEASURE

Whether people trust and use the data.

WHY THAT IS THE ONLY MEASURE THAT COUNTS

A technically excellent platform nobody trusts has failed.


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