Cláudio Gonçalves
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Data Architecture

Data modeling, lineage, and stewardship as the foundation underneath every platform, integration, and identity decision.

Data architecture is the newest domain in this journey and, awkwardly, the one everything else turns out to rest on. Years of monitoring, integration, and identity work kept pointing at the same conclusion: none of the other domains function without reliable data underneath them. Monitoring in particular was a data problem I had spent a decade treating as an alerting problem.

In practice

  • Data modeling, lineage mapping, and master-data domain definition
  • Ownership and stewardship, with retention and privacy alignment
  • Classification and segregation of structured and unstructured data
  • Data governance aligned to identity governance: attribute-based access, entitlements

Why it matters

Every platform here exists to produce, move, or consume data. SAP, PI, Documentum, the IoT sensors. Treat data as a byproduct of those systems and your analytics inherits whatever quality each system happened to leave behind. Treat it as the thing being designed and the rest gets easier to trust.


Where this shows up in the journey