The client was looking to build a near real-time Operations Dashboard for the Operations as soon as the data arrived. Their data was both in structured and semi-structured formats. The semi-structured data was delivered throughout the day in XML or CSV formats. The structured data was sourced from an on-prem SQL Server. The client wanted an Operations Analytics Dashboard built from the above data sets that could show how efficient the operational process is while loading and unloading train cars that load materials in the vessels, how efficient is the handover process from one shift to another, the number of safety incidents, and maintenance over the period, such as daily, weekly, and monthly.
The client used a third-party application to manage their day-to-day work. Building dashboards to measure the KPIs (such as machines on the collection, priority tasks, high priority tasks, early warning on delays, etc.) was a manual, time-consuming, and error-prone task. They were looking to automate the entire workflow and needed the data every 30 minutes to be able to effectively manage their process.
They were unable to build a view of the drivers’ efficiency, and early warning when prioritized pickups could get delayed. To make matters more difficult they had no internal expertise in technical aspects of the application they were using, making requirements gathering a tricky proposition.
The client wanted to automate their Performance Scorecards and Financial Dashboards in Power BI. The requisite data sets were set across multiple data sources such as application database, SharePoint, and Excel files. We also had to fetch data from third-party APIs.
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