Why are Business Intelligence (BI) tools in such demand?

In recent years, there has been greater momentum for Business Intelligence (BI) and analytics tools. The shift stems from the need for a business-led self-service analytics tool that moves away from an IT-led system-of-record (SOR) reporting, enabling faster report creation and decision making. With an increasing need for report accuracy, as well as integration of data from disparate sources (on-premise, cloud-based apps, and 3rd party sources), the demand for powerful BI tools is continuing to grow today.

What We Offer

We help businesses strengthen their decision-making capabilities by applying Microsoft technologies to answer the most important questions facing them.


Our BI Optimization Process

Xelleration engages in a unique process to transform your approach to leveraging data by helping you map out and execute a BI approach that helps you go beyond reporting on past data and into predictive and prescriptive analytics. 

Leveraging the Microsoft platform, Xelleration will help:

Reduce costs associated with dedicating internal teams to manually produce reports.

Shorten decision cycles by increasing end-user data and BI process ownership.

Increase data accuracy by implementing an agile and repeatable process for the production of reports and actionable data.

Facilitate data science and innovation by empowering users with a self-service analytics tool.

Minimize business impact of constantly changing data sources, tools and needs by providing your team with ongoing support.

We provide two approaches to creating your reports and dashboards:

Option 1: Develop Skills In-house

Xelleration coaches your power user community by modeling conversions of existing reports, and/or developing new reports, and enabling power users to effectively leverage BI tools on an ongoing basis.

Option 2: Fully Outsource Development

Xelleration employs an Agile methodology to manage your reporting product backlog and provide support for your end-users.

Factors that affect timeline and cost, include:


  • Quantity and complexity of data sources and reports
  • Data hygiene and standardization
  • Location & accessibility of the data sources
  • Number of departments and end-users

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