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Building a Data Warehouse and Analytics Platform Across Finance, Operations, Maintenance, and Supply Chain for a Fast-Growing Mining Contractor

MiningMining
Industry
Energy & Natural Resources
Mining
Client
One of the Fastest Growing Mining Contractor
Service
Digital, Data & AI
Solution
Data Warehouse and Analytics Implementation Across Finance, Operations, Maintenance, and Supply Chain Functions

The Company is one of the fastest-growing mining contractors in its market, generating operational and financial data across finance, operations, maintenance, and supply chain functions at multiple contract sites. This data had historically been siloed across separate systems with no consolidated analytics capability.

  • Operational, financial, maintenance, and supply chain data siloed across disconnected systems
  • No consolidated data warehouse to support cross-functional analytics and reporting
  • Manual, spreadsheet-based reporting processes slowing management decision-making
  • Inconsistent data definitions across sites complicating group-wide performance comparison
  • Limited ability to identify performance trends and root causes across functions in a timely way
  • As mining contractors scale across more sites, siloed data becomes a growing barrier to timely, informed decision-making
  • A consolidated data warehouse enables cross-functional analytics that single-system views cannot provide
  • Standardised data definitions are essential for accurate, comparable performance reporting across sites
  • Without a modern analytics capability, management decisions rely on lagging, manually compiled reports rather than near-real-time insight
1

Data Landscape Assessment

Assessed data sources and quality across finance, operations, maintenance, and supply chain systems across sites.

2

Data Warehouse Architecture Design

Designed the target data warehouse architecture and data model to consolidate cross-functional data.

3

Data Integration & Pipeline Build

Built data pipelines to integrate source systems into the data warehouse with standardised data definitions.

4

Analytics & Dashboard Development

Developed management dashboards and analytics views spanning finance, operations, maintenance, and supply chain.

5

Rollout & Data Governance

Rolled out the platform with a data governance framework to sustain data quality across sites.

  • Consolidated Data Warehouse Architecture
  • Cross-Functional Data Integration Pipelines
  • Standardised Data Definitions & Governance Framework
  • Executive Performance Dashboard (Finance, Ops, Maintenance, Supply Chain)
  • Site-Level Benchmarking Analytics
  • Phased Rollout Roadmap Across Sites
  • Data Governance & Sustainment Model
  • Self-Service Analytics Enablement for Site Teams
01

Consolidated Data Foundation

A single data warehouse now consolidates finance, operations, maintenance, and supply chain data across sites.

02

Faster Decision-Making

Management dashboards replaced manual, spreadsheet-based reporting, speeding up decision cycles.

03

Comparable Site Performance

Standardised data definitions enable accurate, like-for-like performance comparison across sites.

04

Earlier Trend Identification

Cross-functional analytics help management spot performance trends and root causes sooner.

4
Functions — finance, operations, maintenance, supply chain — consolidated in one warehouse
50%
Reduction in manual reporting effort (approx.)
Multiple
Contract sites reporting through the unified analytics platform
30%
Faster management reporting cycle (approx.)
1
Single source of truth replacing siloed spreadsheets
90%+
Data quality consistency achieved across integrated sources (approx.)

The Company now has a consolidated data warehouse and analytics platform spanning its core functions, giving leadership a single, trusted source of truth across sites. This foundation lets the Company keep adding sites and data sources without losing the ability to see performance clearly across the business.

Digital, Data & AIData WarehouseAnalyticsData GovernancePerformance Dashboard

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