Business case

XLCubed - Advanced Analytics applied to People Segmentation


The Challenge 


       XLCubed Advanced analytics applied to people segmentation
XLCubed Advanced analytics applied to people segmentationThe customer is a not-for-profit organisation. As part of various engagements, volunteers often need to be on boarded and integrated as part of the execution teams. But the selection of volunteers, from databases containing often thousand of relevant profiles, each profile being described using several properties, can be a daunting task. Ideally, a user would filter according to any combination of parameters, to come down to a shortlist of candidates that are all relevant and ready to be interviewed.


 The Solution

To solve this challenge, Evolusys created an Analytics solution, automating clustering of candidates based on criteria selection. The end result is a lightning fast, agile and highly accurate selection tool, that will apply the newest Data Mining and Clustering algorithms to make sense of the raw data. The user can then browse the volunteer database across several, complex, often inter linked criteria, simply from a web browser, and build the list of selected candidates in a matter of minutes. The chosen underlying technologies, not only allowed us to build the solution in an optimised amount of time, but it also ensured performance and scalability, under any condition while remaining easy and engaging to use.



  • Manages very large volumes of data, without lag
  • Create very complex queries and analysis using efficient tools
  • Leverage state of the art, machine assisted clustering and filtering algorithms
  • Use from a simple web browser, no installation required
  • Design intelligent forms, targeted at desktops, smartphones and tablets
  • Integrate and cross reference to several data sources seamlessly
  • And much, much more... 



  • Microsoft Power BI Desktop
  • Microsoft Office 365 (optional) 
  • Microsoft SQL Server for BI (SSAS, SSIS – optional)
  • Microsoft SQL Server 2016 (for On-Prem publishing)

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