Optimizing Fleet Tracking for Vegetation Management with Power BI

Utility Vegetation Management: Data from different sources like Workday, Geotab vehicle details are processed and fed to downstream applications and reporting purposes. Value: Data consolidation and cleansing for quality reporting

A leading vegetation management company struggled with fleet tracking inefficiencies due to the complexity of retrieving trip details from Geotab servers. The slow data processing and reporting delays hindered their ability to make real-time operational decisions.

To address these challenges, we migrated ETL processes from Power BI to Informatica jobs, optimized database queries, and consolidated dashboards for improved visibility. This transformation enabled real-time fleet monitoring, enhanced analytics, and a 98% reduction in data refresh time—from over 3 hours to just 2 minutes.

Impact

📌 Industry: Vegetation Management Services

📌 Key Technologies / Platforms:  SAAS Applications, Informatica, ADF

📌 Key Services:

                          Contract Utility Forester

                          Workflow Management  

                          Safety Services

                          Strategy

                          Data

                          Cloud

                         Privacy & security

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Calculating risk, together

The company relied on Geotab servers to track fleet movements, ensuring vehicles were efficiently deployed for vegetation management tasks. However, they faced several hurdles:

• Complex Data Extraction: Retrieving trip details from Geotab servers required manual intervention and lacked automation, causing inefficiencies.

• Slow Power BI Performance: The dashboards struggled with long refresh times, impacting the ability to make real-time decisions.

• Limited Scalability: With data growing rapidly, the existing Power BI ETL process was not sustainable for future expansion.

• Disjointed Reporting: Separate Power BI dashboards for different regions resulted in inconsistencies and additional maintenance efforts.

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Our Approach: Implementing a Scalable and High-Performance Data Pipeline

To solve these challenges, we designed and implemented a scalable ETL pipeline, ensuring seamless data extraction, transformation, and visualization.

1️⃣ Optimizing Data Extraction from Geotab Servers

🚛 Automated Fleet Data Retrieval

• Developed a robust backend process to extract vehicle movement data directly from Geotab servers, eliminating manual efforts.

• Implemented scheduled data pulls to ensure continuous updates without overloading system resources.

• Ensured data validation to prevent incomplete or incorrect trip details from affecting analysis.

2️⃣ Enhancing Data Processing & Performance with Informatica

⚡ ETL Migration from Power BI to Informatica

• Moved all ETL (Extract, Transform, Load) processes from Power BI to Informatica, significantly improving processing speed.

• Focused on optimizing the Trip Detail Table, which was previously responsible for extended refresh times.

• Achieved a drastic improvement—reducing refresh time from 3+ hours to just 2 minutes.

🔄 Optimized Data Transformation for Power BI

• Instead of directly querying SQL Server databases, we introduced SQL views, allowing Power BI to fetch pre-aggregated data for faster loading.

• Improved Power BI slicer/filter performance by restructuring queries, enabling smooth user interactions without lag.

3️⃣ Power BI Dashboard Consolidation & Visualization Improvements

📊 Unified Dashboards with Enhanced Insights

• Combined multiple Power BI reports into a single unified dashboard, enabling project-based filtering for better fleet tracking.

• Introduced dynamic slicers that allowed users to differentiate data by region, trip type, or fleet category—reducing redundancy in reporting.

• Enabled drill-down analysis, allowing managers to investigate vehicle performance, driver behavior, and trip history in greater detail.

4️⃣ Ensuring Long-Term Scalability & Performance

📈 Future-Proofing the System

• Established scalable ETL processes that can handle increasing data volumes without performance degradation.

• Implemented automated error handling and alert mechanisms to flag inconsistencies in data processing.

• Designed a modular architecture, ensuring adaptability to future system enhancements or additional integrations.

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Results & Business Benefits

🚀 Fleet Data Refresh Time Reduced – From 3+ hours to just 2 minutes, a 98% improvement.

🚀 Real-Time Tracking Enabled – Ensuring managers can monitor fleet activity with up-to-the-minute accuracy.

🚀 Enhanced Power BI Performance – Faster slicers, improved filtering, and better visualization for insightful decision-making.

🚀 Streamlined Operations & Cost Savings – By consolidating dashboards, we reduced maintenance efforts and improved administrator efficiency.

The Impact

✅ Real-Time Fleet Monitoring – Provided fleet managers with up-to-date insights on vehicle movements, enabling faster response times.

✅ Drastic Data Refresh Time Reduction – Optimized ETL processing, cutting Power BI data refresh time from 3+ hours to just 2 minutes.

✅ Improved Data Accuracy & Reporting – Implemented SQL-based views to streamline Power BI reports, reducing query loads and enhancing performance.

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Looking Ahead

By modernizing its fleet tracking system with a scalable ETL pipeline, Power BI optimizations, and Informatica migration, the vegetation management company transformed its fleet management operations.

🌍 The result? Faster decision-making, increased operational efficiency, and an AI-driven fleet tracking system built for the future.

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