Tutte le storie di Visualizations

Let’s explore a chart type that’s likely familiar to most people: the heatmap calendar.

I recently found an article showcasing 2016 in charts, and I really liked the slope charts with the area shaded between the two categories being compared. I found this to be a really cool technique for making a point and telling the story. I wanted to see if I could recreate this in Tableau, so here's how it's done. I'm using the Superstore data in this example.

This is, without question, the most controversial chart type that I present. I almost saved it for last, lest you be offended by the subject matter and decide not to check out the rest of the posts in the series. But I actually get made fun of internally for how much I like this chart, so I’ve worked up a bit of bravery when broaching the subject of this one.

Even if you’re not answering a specific question, you need to help the reader. You need to drive him to insights. To do so, follow these four recommendations.

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 take a look at a chart type that has been growing in popularity amongst the Tableau community: the hex-tile map.

Schemas play an important role in data visualization because they have the ability to make or break the two biggest benefits of visualizing data: reducing time to insight and improving the accuracy of insights. Tap into your audience’s schemas and you improve their experience; disrupt their schemas and you run the risk of leading your audience in the wrong direction.

Make your Tableau viz rain by following these 10 tips.

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.

What a year it’s been for data viz! All throughout the year, we’ve been amazed by the creativity we’ve seen from you, the Tableau community. Not only have you told a wide range of data stories, but you’ve done so in innovative ways that we never would have imagined.

If you haven't used Python before, have no fear—this is definitely achievable for novices. Read on!