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Prime Partners - Entrerprise Transformation Consultant
DATA LAKE & ARCHITECTURE MODERNIZATION

Draining the Swamp: A Governed Lakehouse That Made Every Other Transformation Possible

Client: A multi business

enterprise with 40+ data sources, 300+ report variants, and no agreed numbers [VERIFY profile]

Governed lakehouse outcomes
From data-swamp complexity to governed, reusable data products
Before
Outcome
−80%
Data preparation
5×
×5
Decision speed
300 → 60
Report variants
40–50%
Analytics & AI launch
Data preparation reduction · Decision acceleration · Report rationalisation · New-use-case launch potential

The challenge

An earlier data lake had become a data swamp: forty-plus sources landed raw, three hundred report variants disagreed with each other, and every analytics or AI initiative began with weeks of data archaeology. Finance, sales, and operations each brought their own revenue number to the same meeting.

Why it held

Governance was built into the architecture rather than policed around it — a dataset physically cannot reach the governed layer without an owner, a definition, and a quality score. This engagement became the foundation layer for the client's subsequent AI roadmap.

What Prime did

  • Rebuilt the estate as a governed lakehouse on Nucleus under the data lake and governance practice — raw, curated, and governed-product layers, with quality scoring at every promotion.
  • Established data-product ownership: every governed dataset has a named business owner, a published definition, and full lineage from source to report.
  • Retired report sprawl by rebasing the top decision reports onto governed products first — then switching off the variants they replaced. BigBrain models now train directly on governed data.

Outcomes

−80%

Data preparation effort Published

5×

Faster decisions on governed data Published

300→60

Report variants retired [VERIFY] Engagement figure

40–50%

Faster time-to-launch potential for new analytics & AI use cases [TARGET] range

Gartner research on data management links governed, product-oriented data architectures to materially faster analytics delivery and lower integration cost; the [TARGET] range reflects the conservative end of reported acceleration.

Gartner
Research

What if everyone finally trusted the same data?

We turn fragmented data estates into governed lakehouses—giving every report, analytics model and AI initiative a reliable foundation to build on.

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