All Analyst Stories

Extension activities are a new resource for the free training videos that provide that next step in scaffolding. Each extension activity consists of two workbooks. One lays out the task and any necessary background information, and the matching solution workbook provides detailed step-by-step directions for solving the task. Extension activities build off concepts addressed in the videos and are listed under one or more relevant videos.

Let’s be honest—some variant of bar charts and line charts are the best choices in terms of visualization best practices for the vast majority of the vizzes any of us will ever create. However, I think a chart’s appeal is sometimes more important than the best practices of the visualization you’re showing.

"The skills required for most effectively displaying information are not intuitive and rely largely on principles that must be learned," says Stephen Few in his excellent book Show Me the Numbers. In principle, I agree. But there is a problem: Some of the skills can only be learned by practice. Knowing what makes a purely functional chart doesn't teach you about human psychology and the need to engage as well as inform. Experience of failure and success, learned early on, teaches you as much as books.

When we see great stories of customers leveraging powerful tools and best practices to drive adoption of analytics at scale, it’s something we like to highlight to our community and help share those learnings. GoDaddy is doing just that with Tableau and our data cataloguing partner, Alation.

How do you explore data? What path do you take from opening a data set to publishing a dashboard? Do you go in a straight line or a squiggly path? This week Tableau’s research team is joining Makeover Monday to help answer those questions.

We believe people should not be forced down a straight line, but be able to explore the data, chasing hunches, in order to focus on the best articulation of the data. Knowing more about people’s behaviour helps us improve Tableau. We want you to help us by getting involved in a special experiment next week. The research team are joining with Makeover Monday for a special “advanced logging” week. Collecting multiple log files from people all exploring the data set will give us a unique perspective on people’s paths through the data.

The nerd glitterati of TC16 gathered with one mission: Choose the winner of the Live Hackathon in Austin. At stake? Nothing less than $1,000 and the coveted Trophy of Eternal Glory.

We’re happy to announce the beta release of TabPy, a new API that enables evaluation of Python code from within a Tableau workbook. When you use TabPy with Tableau, you can define calculated fields in Python, thereby leveraging the power of a large number of machine-learning libraries right from your visualizations.

Elections are exciting times for the data visualization and data journalism field. The innovations in each election cycle set the trend for the future of the field.

See and understand your JSON data without data prep! In Tableau 10.1, you can connect to your local JSON files, reason about their structure, and start analyzing.

One great new feature in Tableau 10 is clustering. What was once only available to people who could use complex statistical tools can now be done with a drag and a drop. I know my mean from my mode and what a normal distribution looks like, but like many of our customers, I’m no statistical expert. I wanted to answer a simple question: What exactly is clustering and why would you use it?

You’ve connected to data, created some views, placed them on a dashboard, and now it’s time to share. Before you do, have you considered who you are sharing your dashboard with? Check out these tips and tricks for using device designer (new in Tableau 10!) to let your data shine on phone, tablet, and more.