We have entered a period in human history where the increase in data has far outpaced our ability to understand what the data means. This is a fundamental challenge to all who seek to drive change in their work. What is demanded by this data tsunami is much greater “data literacy” by citizens and information workers.
Learning a tool like Tableau will not only help you drive more change, it is a sure way to increase your value to the job market. Tableau is an increasingly sought after skill by employers.
This Tableau Introduction is meant to help you get started asking better questions from your data and to start better sharing the answers you find.
Step 1. Downloading and installing Tableau
If you have an .edu email address and want to learn Tableau as a student, you are in luck. Tableau offers a free one-year license that can be obtained by going to https://www.tableau.com/academic/students.
Step 2. Register With Tableau Public
After you’ve completed Step 1, go to https://public.tableau.com/s/ to sign up for a Tableau Public account. Click “Sign In” in the upper right and create an account. This account will allow you to share the visualizations you create over the web and allow me and your classmates to view your work.
Note, do not proceed to Step 2 until you’ve downloaded the software in Step 1. The Tableau Public offers a free, limited version, of Tableau software. You do not want this version, you want the version found in Step 1.
Step 3. Start Learning
Once you’ve installed Tableau, follow along with the Tableau Starter Kit here to begin your journey.
In addition to the videos and resources highlighted in the Tableau Starter Kit, Tableau offers free instructor led interactive web seminars to take you to the next level. See here.
The resource pages for Tableau Public, here, offer an additional learning path and provide links to many data sets you can use to learn Tableau.
If you are coming to Tableau with a strong background in Excel, I highly recommend these two videos here and here to help with the transition. Heavy Excel users coming to Tableau often make the mistake of trying to repeat the way that Excel works in Tableau. Tableau offers a much different way of interacting with data than Excel. Rather than recreate the way you approach data in Excel inside Tableau, focus on the questions you want to ask and learn to use Tableau the way it was designed to be used.
Step 4. Datasets to Practice With
Every week, the good folks at Make Over Monday publish a new data set to practice your data chops with. Up to a hundred data enthusiasts will work on creating visualizations based on the dataset and share them via Twitter. At the end of the week, a moderator will highlight lessons to be learned and spotlight a few of the best submissions.
Below is a sample of some of the data sets and the comments offered.
|Topic||Download Dataset||Original Article||Best Vizs|
|Employment Growth in G7 Countries||XLS||Article||Makeovers|
|Factors people report lead to success||XLS||Article||Makeovers|
|Job demand for data skills||XLS||Article||Makeovers|
|Alcohol consumption trends in Briton||XLS||Article||Makeovers|
|American national park visits||XLS||Article||Makeovers|
I invite you to try your hand with a few of these. If you want feedback, please upload your work to Tableau Public (instructions here at bottom of page) and send the URL to paul (at) vizalyst dot com.
Step 5: Online resources
Presenting your Findings: This is a fantastic talk from Professor Simon Peyton Jones on how to write a great research paper. This is a great foundational resource for thinking about data storytelling and can be found here.
See the General Resources listed under the Power Start Workshop postings for more suggestions!