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Customer is a leading wholesale distributor and industrial supplier that specializes in plumbing, heating and air-conditioning, swimming pool and waterwork services, and various construction services. It has presence across all over US and each location work in a decentralized environment.
Customer had recently moved to a cloud DW solution built around Azure Synapse and other Azure services. The financial reports generated from the new system requires a whole lot of manual efforts to compare data from reports generated via legacy systems. This involved a lot of manual intervention to compare data for every month which in turn created a big delay in the whole financial data validation process. Moreover, the solution was not generalized and robust, had too much manual dependency, limited to test data for a single month at a given time and was not scalable to be used across other domains for data validations. Validations were done by exporting data in excels, building logics in Microsoft Access and comparison in another excel workbook.
Our team started with the understanding of the data validation process, the challenges and limitations, and the future use cases which to be catered. Post the discovery sessions, the team proposed a dynamic data validation built in Azure Synapse and digitization of the excel reports using Power BI. All the data exports challenges including 1 month at a time exports, validation logics and rules, and output data ready for comparison was created and driven with the help of metadata tables and SQL stored procedures. The process was generalized to add future cases and was simplified for ease of maintenance and support. The process execution was handled by ADF and email notifications were set up using Azure Logic Apps. Validation reports were created in Power BI to automate and digitize the existing reports and data comparisons were made available to the users for all cases. During the whole project, our team provided all appropriate deliverables including Solution Design, Development logics, unit testing, UAT test case and results, performance and regression testing, user trainings and manuals at appropriate stages of the project.
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