Manufacturing
Data Engineering
Deploying 30+ Power BI Dashboards for a Leading Heavy Equipment Dealer
Our client's massive construction and mining equipment dealership faced a critical operational constraint with consolidating insights. Data was spread across siloed enterprise systems making it manually intensive and required continuous data manipulation. Relying on fragmented architecture to manually aggregate complex operational data created significant reporting delays, degraded strategic visibility, and limited performance tracking.
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Challenge
Solution
The Outcome
The Challenge
A premier heavy machinery enterprise needed to optimize cross-departmental operations but found their scattered, legacy data infrastructure was unsustainable, risking critical inventory bottlenecks and delayed executive decision-making.

Fragmented Enterprise Systems

The inability to natively sync massive datasets across SAP ERP and Oracle CRM, complicated by manual SharePoint entries, severely capped the volume of real-time operational insights leadership could access at once.

Inefficient Resource Utilization

Using specialized analyst teams for routine data extraction and manual formatting led to inconsistent reporting standards and spent highly skilled human labor on repetitive, slow data validation tasks.

The Solution
We delivered a unified cloud data architecture, combining an interactive Power BI frontend with a robust Databricks and Azure backend to automate complex enterprise reporting.

Automated Data Pipelines

‍We architected a robust backend where engineers directly orchestrate daily automated extractions, pulling millions of rows from SAP ERP and Oracle CRM seamlessly.

Scalable Cloud Ingestion

‍The architecture uses optimized Microsoft Azure environments to consolidate the enterprise data smoothly, powering centralized storage from raw financial transactions to global inventory logs.

High-Volume ETL Processing

‍We integrated a unified Databricks environment that automatically transforms raw inputs using Python and Apache Spark (PySpark), allowing for complex data-driven logic based on cross-department rules.

Interactive BI Architecture

‍Powered by Microsoft Power BI, the system immediately visualizes complex transitions across 30+ operational metrics, including dynamic sales dashboards and predictive preventive maintenance (PM) models without latency.

Comprehensive Enterprise Analytics

‍The framework dynamically accounts for advanced operational edges, including conditional equipment monitoring and automated KPI tracking, guaranteeing total organizational visibility and performance optimization.

The Outcome
The enterprise is now able to achieve faster, more consistent operational reporting. Automated data pipelines and optimized cloud architecture have dramatically improved cross-departmental agility.

100% automated enterprise data integration across SAP, Oracle, and legacy endpoints

30+ dynamic, real-time dashboards deployed across sales, service, and procurement suites

90% reduction in manual data processing and routine report generation time

We have been working with Entrans for the last two years and they have played a key role in building our solution. Their expertise and professionalism were evident throughout the development cycle, and we were very pleased with the final product. They have shown enormous skill and vast domain knowledge and their IT expertise is reliable and trustworthy. We would recommend Entrans for anyone looking for quality IT services, delivered in a professional manner
Nikolay Prokopiev
Chief Executive Officer
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