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DSRS Services

We assist faculty research through the execution of statistical and data science methods, providing consultative services and analyses within our computational infrastructure. The College has invested in DSRS and funds the unit’s consultations and other work.

We assess research studies to determine what type of data and computational infrastructure are needed, and we can provide recommendations if the needs are external. There may be a cost for contracting external services. In some cases, researchers can provide their own funding to have their projects going for longer periods of time or to have exclusive help from our interns.

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We can assess and make recommendations for what statistical and data science methods are appropriate for specific research questions. Here are some methods we’ve used:

  • Inferential statistics
  • Social media analytics
  • Text mining
  • Natural language processing
  • Machine learning
  • Deep learning
  • Data visualization
  • Dashboard design
  • Web scraping
  • Data storage
  • Database usage
  • Data cleaning
  • Data gathering
  • Scalable computing
  • Image processing
  • App development


Our director manages student interns who conduct analyses – the core service of DSRS. We use fundamental principles of data science to help deliver research solutions. Our team features students from business, computer science, statistics, and social science backgrounds who bring in data and methods from each of these disciplines


We maintain an in-house library of datasets that are available for Gies Business faculty to use. If specific data are needed to answer research questions, we can assist in locating and acquiring the right data. There may be an additional cost to acquire or license the dataset.

Computational capability

We have our own cloud computing cluster with over 600 cores and over 30TB of storage in addition to access to Microsoft Azure credits. In addition, we use on-campus computation; cloud computing; and custom-built, on- premises computation to assist faculty research. We can help subcontract the analyses to other units on campus, such as NCSA, if certain computational infrastructure is already built or is more cost-effective to use on their side rather than within our office. We help to connect researchers to these resources.

Microsoft Azure

We’re delighted to have been awarded over $160,000 to date in cloud computing credits from Microsoft Azure. This contribution has been instrumental in fostering innovation, facilitating the exploration of new technologies, and enabling large-scale computations for advanced research. In addition, these credits have broadened our ability to provide faculty members with access to high-powered cloud computing services, enhancing their capacity for in-depth exploration and discovery.


Access to these Microsoft Azure credits is also included as part of our services.