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Case study

PAE — Pan American Energy

Dashboards and data models spread across legacy systems, consolidated into one AWS lakehouse with a governance model that gives every asset an owner, a lineage and quality criteria.

Client
Pan American Energy
Industry
Energy
Scope
Data modernization program

Context and constraints

PAE is one of Argentina's largest energy companies. Its reporting had grown system by system: dashboards and data models lived inside the legacy platforms that produced them.

The program set two goals at once: consolidate that estate into a single platform, and make the result accountable, so that every asset on it has someone responsible for it and a traceable origin.

The architecture decision

A lakehouse on AWS is the single place where data lands and is served: Apache Iceberg tables for open, versioned storage; AWS Glue for ingestion and cataloguing; Amazon Athena to query without a warehouse to operate.

Governance is not a document beside the platform but a model applied asset by asset: each dataset and dashboard gets an owner, its lineage back to the source systems, and explicit quality criteria. That is what turns a consolidation into a source of truth.

What the client got

  • Enterprise-wide consolidation of dashboards and data models on one platform.
  • A governance model defined asset by asset: ownership, lineage and quality criteria.

Stack

  • AWS Lakehouse
  • Apache Iceberg
  • AWS Glue
  • Amazon Athena
  • Data Governance
  • Data Lineage

A similar system to take to production?

Talk to the team

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