Asset Management CompanyAsset Management

Asset Management Migration

Hours to onboard

Automated quality

Complex JSON at scale

Overview

From siloed systems to a unified Fabric platform

Asset management data had been scattered across multiple operational systems, tickets, SLA metrics, predictive maintenance signals, and planning data all living in isolation. We consolidated the entire data estate into Fabric, bringing these diverse sources together in a single governed platform. The transformation turned raw operational data into clear, actionable insights and enabled the client's internal data team to own and extend the platform going forward.

Technologies

Microsoft FabricKeyVaultPower BIDevOps (CI/CD)GitAzure

Challenge

What we faced

  • 01Consolidating ticketing and SLA data while ensuring consistency and availability
  • 02Integrating predictive maintenance signals with event-driven, time-sensitive patterns
  • 03Complex planning context involving assets, locations, schedules, and constraints
  • 04Multiple legacy system integrations needed to assemble a complete operational picture

Approach

How we solved it

  • 01Fabric as the unified platform for ingestion, transformation, and analytics
  • 02Automated, traceable quality checks catching issues before they reach consumers
  • 03Azure KeyVault for secure, centralized credential management
  • 04DevOps pipelines with Git integration for reliable, version-controlled deployments

Deliverables

What we built

  • 01Complete consolidation from siloed systems to a unified Fabric data platform
  • 02Unified operational insights spanning assets, work orders, and service performance
  • 03Comprehensive data quality framework with checks embedded across ingestion and modeling
  • 04Specialized handling for complex, deeply nested, high-volume JSON structures

Results

The impact we delivered

New data sources onboarded in hours, not days or weeks

Data issues caught early through automated, traceable quality monitoring

Complex nested JSON structures consolidated and ingested reliably at scale

Platform delivered collaboratively alongside the client's own data team

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