Tools for Data Analysis

In addition to providing the raw data to our campus community, I think the library can take a leadership role in providing the tools and expertise to mine this data into something usable and useful. However, many of the tools that are used to transform data are highly specialized and have a pretty steep learning curve. So I’m going to work to provide an overview of the tools available and focus on those that would be useful in the context of undergraduate education.

Data Tools


Probably my favorite tool and definitely the most accessible to undergraduates. This is probably the best place to start looking at data and could be useful for basic manipulations and visualizations. It could also be a good starting place to talk about the limitations of this tool (size limitations, functional limitations, etc.) and the need for more powerful tools. But this seems like the logical starting point. I’m also amazed at how poorly “digital natives” can navigate Excel. So I think there is work to be done here.


My latest obsession is Tableau and I could easily see undergraduate students using this tool to manipulate and analyze data. I think the learning curve is similar to Excel though the learning process might be more enjoyable for some.


A big step up here. Python is mighty powerful but it is difficult to imagine this being used by undergraduates in a general education course.

Tools I Need to Evaluate

These are tools that I see talked about but lack personal experience myself. Hard to make an informed recommendation before trying them out myself.

  • R
  • SPSS
  • OpenRefine
  • Stata
  • ArcGIS Products

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