- Welcome to the workshop. In Week 1 we will start with an overview of Tableau and learn how to do some basic chart types. Mostly we will be following the Week 1 Workbook linked to below. You might want to have it available for reference, but mostly you will be following along with the instructor. For sure, you will want to download and have available the Week 1 Dataset on your computer.
- More on pie charts (do they really “subtract from knowledge in the world?”)
- Assignment: Download this Makeover Monday dataset and create 1) your choice of visualization and 2) Likert bars showing results. Upload visualizations to your Tableau Public Account.
(Google “Likert Chart Tableau,” Good Post, Good Video, Another Good Video)
(Original Visualization, Makeovers, Top 5, Viz Review Webinar)
- This week we are going to primarily use a dataset that ships with Tableau (the World Indicators dataset under the Welcome Page Saved Data Sources header on the left). We will begin by building on the basic chart types we learned in Week 1 and then extend. Focus will include:
- Messy Data (data cleaning and pivoting)
- Data Table analysis
- Filters (static and interactive)
- Building and sharing dashboards (for best results, make sure you have a Tableau Public account in order to publish your dashboard)
- Story Lines
- A brief look at Tableau Prep (included with your Tableau Academic License)
- Best practices for keeping a project notebook and file naming conventions.
To be determined the week of session. Ideally, we will tackle the week’s Makeover Monday Project together (see below). Assignment will be shared via email and updated on this page.
- Optional: Itching to grow your Tableau muscles a bit more? Try your hand with this dataset while following this workshop workbook
- This week we will continue to build on the chart types and techniques learned in the first two weeks. Possible datasets that we might use might include:
- Makeover Monday 10/6/19 – UK Political Donations (CSV File)
- Sample KPI Data
- WSJ Scripted TV Shows Visualization
- Employment Growth in the US (Article) (Makeovers)
- US Demographic Shifts, Makeover Monday 11/4/18
- Natality in America, Makeover Monday 2017/33 (Article) (Makeovers)
- G7 Quarterly GDP Growth, Makeover Monday 2017/40 (Article) (Makeovers)
- One of the biggest challenges in learning Tableau is actually not figuring out how to use Tableau to make a chart, but what the names for the different chart types. To help with this challenge, we will look at two great resources: The Tableau Chart Catalog and The Tableau Financial Times Chart Catalog.
- Call to Action: Join the Tableau Community and continue your journey using the resources listed below!
- Learning Resources for Students!
- Guides to Different Types of Charts
- Community/Learning Resources (Tableau is not just a great product, it is a great community!)
- Makeover Monday – My top recommendation for learning Tableau! Each Sunday a new dataset is released, and hundreds of people build and share visualizations using this dataset over the week. On Mondays, one of the coordinators gives an hour + YouTube streaming session analyzing the week’s dataset in Tableau (here is a great example focused on comparing two quantities). On Wednesdays, an hour-long “viz review” session is held examining some of the visualizations that were made. On Friday, the coordinators pick their Top 5 favorite visualizations for the week. On Sundays, it begins all over again. Most of this is done over Twitter (#MakeoverMonday, @VizWizBI, @TriMyData).
- Best of the Tableau Web – Nowadays, it seems everyone is a blogger. To get introduced to the wide world of Tableau Blogs, go here, pull down the Category filter and choose Community.
- DC Tableau User Group – monthly meetings, network and find a job
- DC Data Community (multiple events each week)
- Tableau Whitepaper – Visual Analytics Best Practices
- Vizwiz.com – my favorite Tableau Blogger
- Where to Find Data to Analyze
- Tableau’s Post on Finding Data – Gives a nice overview on how to get started on finding and cleaning data. Good resource list at the end.
- Data.Gov – This is a website of pointers to U.S. Government data. In my opinion, it is a little lame. Some of the pointers lead to non-existent or poorly formatted data. The site has very lofty goals even if it does not fully meet them. Nevertheless, it is an important first stop for anyone seeking data about a specific topic.
- Kaggle.com – – A popular data sharing site. Some datasets are well suited for Tableau analysis, others are better suited to different tools/techniques (e.g., machine learning, sentiment analysis, network analysis, etc.). I like this site because it gives a “usability” rating for each dataset and has better search capabilities than other sites (I’m looking at you, Data.World).
- Data.World – Another popular data sharing site. Content is posted by users and has varying levels of coverage and quality.
- Data is Plural – This is a highly-addictive weekly email providing links to a wide-ranging and idiosyncratic list of datasets. A spreadsheet of past datasets listed can be found here. Take a second and look at the different types of datasets that are out there in the wild (start at the bottom for most recent)!
- Tableau Sponsored Learning