According to Glassdoor.com the ninth best job in 2015 is going to be that of the Data Scientist. This is a job that pays very well, is in high demand, has excellent career opportunities and… it hardly even existed just a few years ago. As we continue to collect more and more data about every possible facet of life on this planet (and beyond), the ability to decipher and understand the vast amounts of information is becoming more and more essential. So how do we begin developing the Data Scientist in our students? How do we encourage students to be inquisitive about data and be able to spot trends and patterns?
A Quick Look
1. Scissors, paper and glue
It’s easy to expect that technology can just suck in data and spit out pretty charts and infographics. The reality is that without careful thought and understanding, visualizations can be confusing, misleading or in many cases completely useless. To try and highlight this point, have your students create their first visualizations using physical materials. This is a great way to build simple models where the tactile act of creation will encourage students to take more time to fully understand and comprehend their data. For an extra challenge and dose of creativity, try asking your students to use material that is relevant to to their subject data (ie. A nutrition infographic made of fruit, etc.).
2. From Paint to Photoshop
If you are looking for a digital approach, the vast majority of professional graphics are created using imaging tools such as Photoshop. Because there are limitations in cost and complexity I would also suggest free/cheap alternatives such as Microsoft Paint, GIMP, Pixelmator and Google Draw. Image creation can be quite finicky and time consuming for students, so my tip is to take advantage of pre-made graphics and icons from sites such as The Noun Project and IconFinder.
3. Presentation Tools
Often overlooked for graphical creation, presentation tools such as PowerPoint, Keynote and Google Slides offer a good balance between price and simplicity. If your students are looking to create simple data visualisations or if you don’t want them wasting time with fancy filters and effects, presentation tools are definitely the way to go.
4. Excel and spreadsheets
Once we start getting into serious data analysis and visualization it’s time to bring out the big guns. While Excel and other spreadsheet applications (such as Google Sheets) have the ability to output charts and graphs, their visualization capabilities can be somewhat limited. Try having your students use spreadsheets to refine and filter their data and then use more graphical tools to present the results in more engaging and informative ways.
5. Specialist tools and sites
Once your students are really in control their data and are showing a genuine confidence in the field, you can encourage them to go on and explore specialist data analysis tools such as Tableau and Qlik (as well as 36 more here). While this software can complicated and expensive, the visualization possibilities are endless.
Links and Next Steps
- Open Data Sources
Feature image adapted from image courtesy of Flickr, Pai Shih.