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Data Analysis Tools

This is part 1 of a 5 part series on Data Analysis Tools.

This week I’ll show you how to use a few of the various data analytics tools available to compute simple statistics and visualize your data. There are a number of tools available, and I will cover the following four by showing you how to create some of the metrics and charts I’ve talked about the last few weeks:

  • Microsoft Excel
  • Google Sheets
  • SPSS
  • R

In addition to showing you how to do analysis and charting in each tool, I’ll touch on a few of the pros and cons that I’ve found in my experiences.

It can be hard to decide which tool to use given how many are available. One primary difference between the tools is the degree to which a user is provided a graphical interface with which to interact. Microsoft Excel and Google Sheets are used primarily via their graphical user interface so you can quickly explore and engage with your data – changing one input will immediately update all of your outputs. R, on the other hand, is a full programming language that takes more of an effort to get started using, but once you learn how to code you can do sophisticated analyses and produce powerful visuals. SPSS is a middle ground between these extremes in that it provides users with point-and-click features that beginners will appreciate, but also gives you the code to generate your analysis and plots so you can replicate or edit in the future.

You might not be familiar with all of these tools and be interested in learning how to use a new one. I’ve found the best way to learn is to force myself to conduct a small project using the new tool. When I only study how it works or use sample data, it’s hard to prioritize or persist in my learning. But when I have a real business deliverable on the line, I make the time to learn how to use the new tool.

I find the best way to demonstrate these tools is via a short video. So, go grab some popcorn and enjoy!

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The Data Analysis Tools series