The Challenge
Vehicle operations data already existed in a client-owned data lake. The requirement was to make that data easily and securely available to a 3rd party aggregation and visualization service provider via a secure REST endpoint.
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.
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