Enterprise Data Hub Modernization for Operational Visibility

Overview

Delta Mechanical operates one of the country’s largest plumbing-service organizations, serving Home Depot customers across multiple states. But their operational ecosystem - ServiceTitan, Home Depot systems, Paylocity, Sage, and internal tools - generated fragmented data that couldn’t easily be combined. Delta partnered with i-ology to build a modern Data Hub that unifies every critical data stream into a single, actionable system.

Spreadsheet

The Challenge 

  • Data was fragmented across third-party systems, resulting in slow, manual, error-prone reporting cycles.

  • Leadership lacked real-time visibility into revenue, job profitability, and technician performance.

  • Duplicate data entry and inconsistent data models made cross-system reporting unreliable.

  • Manual Excel-based reporting consumed significant analyst time.

  • Delta needed a scalable, automated, and future-ready analytics architecture.

The Approach

i-ology partnered with Delta Mechanical to build a unified, automated Data Hub that becomes the single source of truth for operational, financial, and workforce analytics.

Discovery and Strategy

  • Engaged executive, finance, and operations teams to define KPIs for revenue, labor efficiency, profitability, and job duration.

  • Conducted a full data-system audit to identify integration points, schema conflicts, and quality gaps.

  • Mapped all data flows across ServiceTitan, Home Depot, and Sage.

Data Integration and Standardization

  • Built secure Azure Data Factory pipelines to automatically ingest data from each upstream system.

  • Applied business-rule logic to resolve inconsistencies and unify identifiers.

  • Automated quality checks to improve accuracy and reduce manual cleanup.

Data Hub Architecture and Modeling

  • Designed a star-schema Azure SQL warehouse optimized for analytics, self-service, and future scalability.

  • Ensured all fact and dimension tables aligned with business KPIs and operational reporting needs.

  • Implemented data lineage tracking to improve transparency and auditability.

Enterprise Reporting and Decision Support

  • Delivered Power BI dashboards that surface actionable insights across operations, finance, labor, and service metrics.

  • Implemented role-based access controls to govern data visibility by department.

  • Enabled leadership to transition from reactive reporting to real-time, insight-driven decision-making.

Data Hub

The Outcome

  • Transformed siloed data into a unified, automated analytics environment.

  • Reduced reporting time from days to minutes.

  • Improved revenue forecasting, job profitability analysis, and technician performance insights.

  • Created a scalable data foundation supporting predictive analytics and automation.

Technologies Used

Azure Data Factory • Azure SQL (Star Schema) • Power BI • REST APIs • ServiceTitan API •  Sage Integrations

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