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enterprise architecture · data architecture · lakehouse

Enterprise Data Platform

This enterprise data platform diagram combines finance, operations and HR data in a shared lakehouse. A data-integration function supports the platform, while data governance makes ownership and controls visible. The lakehouse serves business-intelligence and data-science consumers. This is a useful enterprise architecture view when the goal is to align data domains and users around a common platform rather than describe the detailed pipelines, transformations or access policies.

Type Control-systems block diagramStandard Ogata / standard controls textbook conventionEngine schematex-blockdiagramUpdated 9/24/2026
Enterprise Data Platform
Drawing preview
The request

“Create an enterprise data platform with finance, operations and HR systems, data integration, an enterprise lakehouse, data governance, business intelligence, and data science.”

Then tryAdd a customer-data source connected to data integration.Add a data catalog connected to the enterprise lakehouse.
What is in this drawing

Read the decisions behind it.

01Source domains

Include finance, operations and HR systems.

02Shared foundation

Centralize curated information in a lakehouse.

03Governance

Make data stewardship visible alongside storage.

04Consumers

Serve both BI and data-science work.

Use it for enterprise data strategy and platform discovery.

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FAQ

Common questions

What is an enterprise data platform?

It is the shared set of data services that collect, govern and serve information across business domains.

Why show governance separately?

It makes accountability and controls visible rather than treating them as an implied storage feature.

Who uses a lakehouse?

Business-intelligence users, analysts, engineers and data scientists can consume governed data from it.