Case Study: Intelligent InSites

Overview:

Intelligent InSites is a leading software company that is transforming healthcare operations with real-time operational intelligence aimed at improving care, enhancing the human experience and increasing efficiency. Their own Real Time Location Services (RTLS) software provides a wide range of solutions for healthcare systems, from asset management to patient workflow, environmental monitoring, infection control, and more.

Challenge:

The RTLS software, however, did not have business intelligence capabilities. Something their management team felt was vital to not only improve the capabilities of the product but to also steer the company in a new data intelligence driven direction. They needed analytics coupled with their operational data the RTLS software already provided. This would allow healthcare administrators the ability to not only track their assets but to efficiently utilize their assets by determining peak usage and shortages. They needed to implement these additional features to their product’s capabilities quickly in order to continue to meet customer needs, to fulfill the terms of client contracts and to increase and improve their service offerings. They teamed with Inquidia Consulting to implement a solution.

Approach:

Intelligent InSites contracted Inquidia to recommend and execute a comprehensive big data and business intelligence solution. Inquidia collaborated with Intelligent InSites to implement the three-phase project. During phase one Inquidia leveraged Pentaho Data Integration and created the exact dimensional combinations required for equipment count & usage information into a Data Mart for analysis and reporting.

Phase two required the implementation of Pentaho CDF (Community Dashboard Framework) visual analytics technology providing an easy to use set of dashboards that give the user easily ingestible data that can be acted upon in a timely manner.

Lastly, phase three required a fundamental redesign of the cubes using Pentaho Analyzer. This was needed to alleviate many of the performance and functional issues Intelligent InSites has been experiencing.

Results:

Intelligent InSites now has the capability to analyze peak equipment counts and usage trends in ways that will allow their clients to better manage where assets will perform best, and resolve losses. They went from a labor and time intensive initial load process, sometimes taking up to a month, down to just four days. Reporting source data was moved from a relational structure to a modern data mart supported by an analytic column store database providing greater performance and measurement abilities. They now also have the competency to sell to their clients a self-service BI component providing analytics that can be shared across the enterprise.

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