IoT data lake on Azure infrastructure | HCLTech

IoT data lake on Azure infrastructure

HCLTech helped the client increase profits by leveraging vehicle telemetry data for route optimization and enhancing driver performance.
5 min read
5 min read


Our client, a leader in transport and logistics based in Budapest and operating across Europe, utilizes an onboard system with an extensive array of telemetric sensors to collect and store data about each vehicle. To be able to effectively leverage such a massive amount of data to drive business decisions, the company needed a solution to feed the data into a data warehouse, and from there into a tool that would enable analysis, feedback and decision-making.

The Challenge

Data migration of telemetry data

The client wanted to migrate all telemetry data from the IoT device provider’s system into Azure.


The Objective

Deriving business value from telemetric data

To leverage the telemetric data from the vehicles and make informed business decisions, the client needed to solve a variety of data architecture and reporting issues:

  • Building a SQL data lake for storing the data
  • Building tabular models and reports incorporating ML models and advanced analytics solutions
  • Designing and implementing an alert-based solution
IoT data lake on Azure infrastructure

The Solution

Data migration and reporting

  • Our team designed and implemented a loading logic that can query XML files through REST API every minute or every five minutes, depending on vehicle location, then parse and forward them into an SQL Server database without requiring another call. This solution relied on custom-developed software written in C# called by a scheduled process leveraging Azure Functions
  • Created detailed data dictionary for previously unused data to build the Power BI reports. The team’s business analyst created the necessary documentation, which the architect then used to design the data mart layer
  • Using the data tables available in the new data mart, the team’s Power BI developer created the requested reports in an Agile process, through multiple iterations, working with the prospective users
  • The reports included heatmaps and combinations of KPI-based and visual representations of routes for plan-fact analysis
  • Our team designed a highly flexible framework to generate rules-based alerts in Azure ecosystem

The Impact

Cost savings and better profits through improved infrastructure

  • Due to a solid and robust reporting and alerting framework that the solution provided, the client was able to leverage extensive vehicle telemetry data to improve decision-making
  • Dispatchers could rely on broader route and vehicle information when issuing orders and the company had more data to optimize route planning, assess driver performance and incentivize preferred driver behavior
  • These improvements to business-critical processes helped the company achieve cost savings and, ultimately, increase profits
  • The client also relied on the framework for management reporting and leveraged it to build ML models for advanced analytics