ProCogia helped process third party Vehicle Operations Data

Company Information

Facing the challenge of efficiently managing and analyzing extensive vehicle operations data, a leading global shipping company sought to refine its Azure-based data platform. ProCogia was enlisted to leverage its expertise in data engineering and consultancy to optimize data ingestion, processing, and accessibility. The goal was to create a scalable, cost-effective solution that adhered to industry best practices and facilitated easy access to critical telemetry data.

The Challenge

The shipping client required a solution that could seamlessly ingest and process large volumes of third-party vehicle operations data without the continuous operation of resource-intensive Spark clusters. The challenge was to construct a system that was both efficient in handling data in the Databricks Delta format and scalable enough to meet the client’s growing data demands. Additionally, the solution needed to embody best practices in software development and testing to ensure reliability and maintainability.

Procogia’s Approach

The client, a large corporation operating in the marine/shipping industry, had already started building a data platform in Azure where all data was curated using the Databricks Delta format. A consultant specializing in Azure and Databricks was brought in to analyse the requirements and existing platform.

To serve vehicle operations data, an Azure web app was constructed in Python using Pandas and Flask. The Databricks Standalone library was used to access the telemetry Delta table, removing the need to have an expensive Spark cluster running 24/7.

In doing so, ProCogia introduced the client to industry best practices for developing, unit testing and deploying Python web applications.

The Results

ProCogia delivered a stable, highly scalable, protected REST endpoint, which provided an excellent template for similar applications in the future.

We introduced and demonstrated industry best practices for developing and unit testing Python and PySpark code.

The solutions were fully unit tested, documented and deployed into the client’s production environment as an integral part of their data platform.

Services Used

Data Engineering

We partner with all major cloud providers, allowing us to adopt a data-agnostic approach focused on delivering tailored game-changing solutions.

Data Consultancy

We provide data consultancy to organizations to optimize your investment in people, processes, and technology. This is typically through data strategy engagements, roadmaps, transformations, and independent technology advice.


Through the development and implementation of a Python-based Azure web app for the ingestion and processing of vehicle operations data, ProCogia substantially enhanced the data management capabilities of the global shipping client. This project not only streamlined data accessibility and processing but also established a foundation for scalable, best-practice-driven application development within the client’s data platform. ProCogia’s expertise in data engineering and consultancy has thus enabled the client to achieve significant advancements in data strategy, efficiency, and operational scalability, positioning them for continued success in the competitive shipping industry.

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