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Enterprise Data Migration, Data Analytics & ERP Modernization for Global Engineering Organization

Case Study Summary

Client: Global Engineering & Construction Organization
Industry: Engineering, Construction & Environmental Consulting
Engagement Duration: 12+ Months Role: Data Architect / Analytics Manager
Team Size: 8–10 (Data Engineers, BI Developers, Application Support)

Impact Metrics:

  • Reduced incident response time to ~15 minutes and resolution to 1–4 hours across global regions.
  • Achieved 30% reduction in customer service overhead through automation of user provisioning integrated with ServiceNow.
  • Successfully migrated financial data from legacy systems to BST ERP for 15+ new LATAM & EU legal entities.
  • Automated secure SSRS report access provisioning using PowerShell and .NET, eliminating manual intervention.
  • Enabled consistent monthly and annual financial close reporting across ERP and dependent systems.
  • Established an automation-led roadmap targeting 40% improvement in customer satisfaction by enabling staff to focus on higher-value analytical and client-facing work.

We aimed to increase the customer satisfaction by 40% over the next three years through automations, enabling the staff to focus on more rewarding roles and build better relationships with clients.

Business Problem

The organization relied on a local legacy software as the system of record for financials, projects, and operational analytics supporting thousands of capital projects globally across engineering, construction, and environmental consulting operations.

As data volumes and reporting demands increased exponentially, the analytics ecosystem faced mounting challenges that threatened operational efficiency and strategic decision-making capabilities.

Key Challenges:

Analytics at Enterprise Scale

  • 8,000+ global users across multiple time zones depended on financial and project reporting
  • Near real-time expectations for critical business decisions, but systems designed for batch processing
  • Thousands of capital projects simultaneously active, each requiring detailed cost tracking and forecasting
  • Performance degradation during peak usage (month-end, quarter-end, project milestones)
  • Limited concurrent user capacity causing report queuing and delays

Fragmented Reporting Landscape

  • 1500+ SSRS reports built over years with no governance or standardization
  • Multiple data pipelines extracting from ERP with inconsistent transformation logic
  • Conflicting KPI definitions across finance, operations, and project management teams
  • Different reports showing different numbers for the same metrics, eroding trust in data
  • No single source of truth for project performance or financial health

High Manual Effort & Data Quality Issues

  • Finance teams spending 40%+ of time on manual data reconciliations instead of analysis
  • Project managers maintaining shadow systems (Excel spreadsheets) due to lack of confidence in ERP data
  • Data correction workflows requiring extensive back-and-forth between finance, operations, and IT
  • Month-end close process delayed by data validation and reconciliation requirements
  • Historical data restatements creating confusion and additional rework

Legacy Technology Constraints

  • Local platform struggling to keep pace with business growth
  • Limited scalability for expanding project portfolio and user base
  • Inflexible data model requiring extensive customizations for new business requirements
  • No self-service capabilities forcing business users to rely on IT for every report request
  • Lack of modern analytics features (predictive insights, mobile access, interactive dashboards)

Migration & Transformation Pressure

  • Merger-driven mandate local system transition to BST ERP within 24 months
  • Merger-driven mandate BST ERP to transition to Oracle ERP within 18 months
  • Decades of historical data requiring preservation with full analytical continuity
  • Zero tolerance for data loss during migration due to regulatory and audit requirements
  • Business continuity imperative - no disruption to ongoing project reporting during transition
  • Need to maintain dual systems during migration period, doubling support burden

Decision-Making Limitations

  • 1-day reporting lag preventing timely course corrections on troubled projects
  • Limited visibility into project profitability until after costs already incurred
  • Inability to forecast cash flow accurately across multi-year project portfolios
  • No predictive analytics for identifying at-risk projects early
  • Executive dashboards requiring manual assembly from multiple disparate sources

Operational Impact

  • Project overruns due to delayed visibility into cost variances
  • Revenue recognition delays caused by data reconciliation bottlenecks
  • Audit findings related to data inconsistencies and lack of controls
  • Lost productivity across finance, project controls, and operations teams
  • Growing frustration among business stakeholders with analytics capabilities

Transformation Pressure: A merger-driven move to Oracle ERP required preserving decades of historical data with full analytical continuity, auditability, and zero data loss.

Our Approach

Delivered a data-analytics–first ownership model across the ERP ecosystem, strengthening data foundations, modernizing BI capabilities, and enabling a seamless transition to Oracle ERP without disrupting analytical workflows.

Data Platform & Database Engineering

  • Managed enterprise-scale SQL Server environments supporting transactional, reporting, and analytical workloads.
  • Designed optimized schemas, indexing strategies, and partitioning to support large-scale financial and project analytics (100–200 GB active data).
  • Developed advanced T-SQL and PL/SQL scripts for data validation, reconciliation, historical restatements, and audit support.

Enterprise BI & Analytics Enablement

  • Owned and optimized an analytics estate of 1500+ SSRS reports, 50+ SSIS pipelines, and SSAS multidimensional cubes.
  • Implemented standardized semantic models and KPI definitions to improve consistency across finance, project controls, and operations.
  • Enabled near real-time insights through automated ETL scheduling and cube processing.
  • Transitioned key analytical workloads to Power BI, improving usability and self-service analytics for business stakeholders.

Data Automation & Quality Engineering

  • Built automation frameworks (RPA + scripts) to eliminate repetitive data preparation and correction tasks.
  • Implemented proactive data-quality checks, monitoring, and alerting to reduce downstream reporting errors.
  • Reduced recurring analytics-related incidents by identifying root causes and stabilizing upstream data pipelines.

Analytics-Led ERP Migration to Oracle

  • Led the analytical workstream of the ERP migration, ensuring reporting parity and historical continuity between BST and Oracle ERP.
  • Performed deep data profiling, mapping, and transformation to preserve analytical hierarchies, KPIs, and trends.
  • Designed reconciliation dashboards and audit reports validating migrated data across multiple cutover cycles.

Results & Impact

Analytics at Enterprise Scale

  • Supported analytics and reporting for 8,000+ global users across multiple time zones.
  • Delivered stable, high-performance analytics across a 10-server ERP and BI ecosystem.

Improved Data Trust & Efficiency

  • Reduced reporting-related incidents and support tickets by ~25% through data standardization, knowledge articles and automation.
  • Significantly reduced manual reconciliations for finance and project teams.

Migration Without Analytical Disruption

  • Achieved 100% validated data accuracy during Oracle ERP migration with no loss of historical analytical context.
  • Ensured uninterrupted access to financial and project analytics throughout the transition.

Better Decision-Making

  • Improved executive visibility into project performance, financial health, and operational KPIs via standardized dashboards and cubes.
  • Enabled faster month-end and project reporting cycles.

Solution Overview

• End-to-end data architecture (ERP → DW → BI)
Architecture Diagram

• SSAS cube and semantic model diagrams
• Power BI executive dashboards
• Data migration reconciliation and audit dashboards

Tech Stack

  • Data & Analytics Platforms
  • Microsoft SQL Server
  • Azure SQL Database
  • Oracle Database
  • BI & Data Engineering
  • SQL Server Integration Services (SSIS)
  • SQL Server Analysis Services (SSAS – Cubes)
  • SQL Server Reporting Services (SSRS)
  • Power BI
  • Azure Data Factory
  • Azure Functions
  • Legacy Systems
  • BST Enterprise (Legacy ERP)
  • Oracle ERP
  • Automation & Development
  • RPA tools
  • Custom data validation and automation scripts
  • SDK-based integrations Mostly (C#.Net based)

Additional Context

  • Close collaboration with stake holders and customer service team
  • Ongoing knowledge base expansion
  • Future plans include implementing feedback mechanism

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