Some Basic Thoughts on Data Visualization

Data visualization is the art and science of clearly communicating data in a way that is easily digestible to the end user. It goes without saying that there is so much data available now. But effectively making sense of that data is critically important. That’s when data really becomes useful information.

Excel can do some things. You are all likely familiar with their built-in line graphs, pie charts and other visualizations. But it is limited in the amount of data you can work with and the customization of visuals. For many scenarios it just fine.

But there are times when one might have more data to work with or perhaps does not have a great way to get data to Excel in the first place. There are tools out there like Tableau that can connect to APIs (or you can import the data) and have a rich library of visualizations and ways to customize them. Tableau in particular has a free “Public” version available however the output will be placed on their website for anyone to see. If you are a business or agency that wants to keep your data private, a paid version is out there as well.

Recently Google announced their version of Tableau — Data Studio. There is a free version here as well and I think you can choose to keep your data private. However, at least as of June 2016, it only connects to other Google platforms. If you want to pull other data into the user interface, it is possible, but you first need to get it into Google Sheets or Big Query, which is a Google SQL database more or less. Big Query is its own topic for another day.

I have only scratched the surface on what is out there. For R users, you can download and work with libraries like ggplot2; QlikView is another Tableau-esque tool; and on and on. Check out this website for a few more examples, which are cleverly broken out tools for developers and non-developers:

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