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# How a utility turned five siloed asset systems into one foundation for asset health
- URL: https://www.agilebrainsconsulting.com/case-studies/utility-unified-asset-health/
- Published: 2026-10-23T14:49:28.000Z
- Updated: 2026-10-23T15:13:29.000Z
- Description: Asset data lived in five systems that didn't talk to each other. Agile Brains engineers helped build one governed data foundation that puts self-service asset analysis in engineers' hands and sets up predictive maintenance.
- Author: Lara Hill
- Tags: #case-study, Utilities

A large East Coast electric and gas utility couldn't answer basic questions about its own network assets without slow, manual work. Working alongside a leading consultancy, Agile Brains engineers helped build the unified, governed data foundation that changed that, and opened the door to predictive maintenance.

## The challenge

The utility's asset information was scattered across separate systems for work management, asset records, inspections, lab testing and metering. None of them talked to each other, so even a simple question, such as which work items have no inspection history, meant slow, manual data wrangling, and the answers couldn't always be trusted.

For an Asset Reliability and Resilience program meant to reduce network risk, that was the bottleneck. Without a unified, governed foundation, neither everyday asset analysis nor any future predictive use case was really possible.

## How we helped

Agile Brains partnered with a leading consultancy on a joint team, with our engineers embedded across the workstreams and doing much of the hands-on build.

![Diagram: five source systems flow through bronze landing, silver hub and gold electric-asset layers into self-service analysis, with a governance and lineage band beneath.](https://storage.ghost.io/c/e4/2d/e42df399-b545-4436-aee1-6737869588bf/content/images/2026/10/case-utility-asset-health-web.jpg)

**A medallion architecture on Azure.** Data moves through a bronze landing layer, a silver hub and a gold electric-asset layer, fed by configurable, reusable low-code ELT pipelines that replicate from each source system daily. A fault-redundant orchestration workflow on Databricks manages dependencies across workstreams and keeps the platform within its service levels even when an individual job fails.

**Governance built in, not bolted on.** Nine validation rules and 15 defined critical data elements enforce quality, and all 74 tables are cataloged with full lineage in Microsoft Purview, so every figure can be traced back to its source.

**Self-service for engineers.** A Power BI report lets Distribution Engineering run ad hoc asset analysis directly, without a data team in the loop.

**Written down to last.** Source-to-target mappings, an entity-relationship model, a business-process matrix, development standards and 12 design and requirements documents leave the platform maintainable and extensible long after the engagement, by the utility's own team.

## The result

Distribution Engineering can now answer questions directly that used to take manual effort, such as finding work items with no inspection history. Asset-data transformations that were built by hand now run in the pipeline; one routine metric derivation alone takes about 30 minutes less. Validation rules, defined critical data elements and full lineage mean the data is correct, traceable and timely.

The unified model also makes the next use cases feasible: equipment forecasting, open-mains backlog reduction, primary feeder analysis and predictive maintenance. The engagement delivered the foundation; those predictive use cases are what it now makes possible. It is one foundation built from the kind of enterprise [data-products strategy](https://www.agilebrainsconsulting.com/case-studies/utility-data-products-strategy/) that tells a utility what to build first.

**By the numbers**

- 5 source systems unified into one asset data model
- 74 tables across a three-tier medallion architecture
- 2,267 source columns mapped into a single governed structure
- 9 validation rules and 15 critical data elements
- All 74 tables cataloged and lineage-tracked in Microsoft Purview
- 12 design and requirements documents, plus development standards