Project Summary

Cloud-Based System & Custom Reporting Delivers Comprehensive View of The Customer

Cloud-Based System & Custom Reporting Delivers Comprehensive View of The Customer

A well-known consumer packaged goods (CPG) organization specializing in pet food approached Imaginet to implement a new cloud-based system for their consumer affairs office. Their existing on-premises environment had a local database, server, and data model that had been in place for over 15 years, and they planned to decommission the legacy server. The customer service system collected data daily from the client’s contact centre (from phone calls, emails, and the consumer web portal). Imaginet imported the call centre data, including images submitted by consumers to support their complaints, and created a user-friendly model that allows the client to produce reports.

We sourced data from SharePoint Document Library files and XML files (from an SFTP Server hosted by the third-party contact centre), leveraging Azure Data Factory pipelines to store the files in Azure Storage and import the data into an Azure SQL Database. We identified reports to migrate from Microsoft Excel and earlier Power BI workspaces that used the on-premises SQL Server database and analysis model. In Power BI, we assembled dataflows and datasets – utilizing them to compose a robust set of reports that the client can easily pull or customize to suit their needs.

Our comprehensive reporting validation phase included various business teams to compare different versions of the reports and ensure accuracy. As a result of regular mentoring with blended team members, we provided training and knowledge transfer to the client’s development team.

Imaginet built a cloud-based customer service analytics model and reports so the client could retire their legacy server on time. Now, they have a complete picture of their data and can gather, organize, and interpret consumer feedback, save time and effort generating reports, and gain insights from their quality indicators.

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Technologies Used

  • Azure Data Factory
  • Azure DevOps
  • Azure SQL Database
  • Azure Storage
  • Microsoft Excel
  • Power BI
  • Power BI Desktop
  • SFTP Server
  • SharePoint Document Library
  • Visual Studio
  • XML

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