Fleet Management Businesses requires an evaluation of various parameters to cut costs. The usage of predictive reporting helps assess and analyze real-time data. Fleet vehicle data helps plot the predicted profitability v/s actual profitability per fleet.
Read-on to learn how our US-based enterprise customer benefited with real-time report analysis. They have 25+ yrs. of fleet management experience.
As their Talend integration partner, Rishabh Software helped streamline 7 billions of data generated every week. Also, it supported the creation of actual reports with accurate inputs for SAP Business Object. Further, we assessed the quality of delivery services to grow their customers.
The primary objective of the Talend data integration project was to manage the real-time data by the fleet vehicles and minimize the data redundancy for generating accurate reports. Our customer had different types of vehicles as a part of its fleet, and they were managed through different kinds of engagements like leasing the vehicle, on rent, daily commuting vehicles, heavy load vehicles, transportation, luxury cabs, corporate tie-ups and various other business dealings. The customer’s profitability or revenue was calculated based on factors like fuel consumption, driver’s payments, and maintenance of the vehicles, inventory and other essential investments. Predictive or forecasting reporting was used by the management team to assess the daily revenue generation & profitability activity, and they required to match the actuals v/s predicted reports to streamline their business.
Rishabh Software’s big data team analyzed the current system architecture and finalized Talend to streamline the data processing. The approach used was divided into various segments handling the data.
In a fleet company, the number of data records generated per hour is in millions. The very first requirement was to create NoSQL Database models to manage and store such vast data.
With Talend data integration, our team solved the complex architectural data flow for new and existing records. Different data flows were designed for a full load and incremental load. The full load flow was to be operated at the start of the daily load, while incremental flow was monitored by the audit dates of the data, resulting in 150+ Talend jobs.
To meet the customer’s requirement of managing real-time and generate accurate business reports, teams of 18+ data engineers were involved in automating data extraction from the IoT, vehicles, and database, creating different structured blocks and database for the new vehicle users and update records for the existing users. Apart from the order information, transaction history regarding investment was also tracked using Talend. The transformed data were fed into NoSQL databases to generate business reports.
US Based Fleet Management Enterprise
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