Check out the video at the bottom of this post to learn more about the value of incremental visual analysis.

Note: The following is a guest post by Tableau Zen Master Kelly Martin.

Blank stares, then...huh?

That's what I get when I say "visual analysis." People tend to think I'm talking about making a chart. I am, but more than that, I'm talking about exploring data visually with Tableau.

Tableau co-founder Chris Stolte gave a great talk on this topic a few years ago. The video is embedded below, and I highly recommend you watch his brilliance in action.

Recently I was given a Tableau workbook to enhance/fix/rejig. It had more than a dozen data sources and a dozen charts. Now, a dozen charts is nothing for Tableau, yet the dashboards were taking forever to load. And the filters weren't working in seemingly-magical ways.

It took me a while to figure out the underlying logic of the workbook. And then I realized that the analyst was still thinking like someone who only has Excel as an analysis and presentation tool.

The Excel logic goes like this:

1. We get a problem or request.

2. We think of the chart we'll create in Excel.

3. We go about getting the data into the table shape we need and perform the calculation(s) on the measure as needed.

4. We make the chart.

So the person who had built the Tableau dashboard had essentially created a bunch of pivot tables, put them on separate worksheets, then connected each to Tableau to make the charts.

This is not crazy; rather, this would be the most efficient way to do it in Excel world—make a bunch of tables, then make the charts.

So, how to unbend the old Excel mindset? In short, free your mind and the rest will follow. ♫

Connect to all the data just as you would to make a pivot table. But don't try to make just one specific chart!

The visual-analysis logic goes like this:

1. We get a problem or request.

2. We connect to the data.

3. We explore the data VISUALLY. Very quickly, we can make a ton of charts (by clicking through Show Me), add dimensions, play, and see what the data has to say. We can uncover insights in relation to our problem/question/goal.

4. We combine the charts on a dashboard to communicate the results.

Did you notice the big difference in these two processes? Visual analysis doesn't begin with the presumption of the outcome or answer.

Wrap your head around that for a moment. I'll bet you didn't think you were presuming the outcome with the Excel process. But by reducing the data into a certain state for a predetermined presentation table or chart, you may have missed a lot of insight.

How often do you get asked to give a stacked bar chart or a pie chart of the data? That's because the requester has a hunch that the chart will show the answer to a problem. Sometimes it might. But if you visually explore the data with Tableau, I'll bet you'll find a whole bunch of new insights. It's never been so quick or easy with other tools. That's because they weren't designed for this.

So watch Chris's video below. Give it a think. And don't be afraid to go crazy with your data!

Check out additional works by Kelly Martin on Tableau Public, on Twitter, and on her blog, VizCandy.


This video tell us the way how we need to approach the data and how effectively come to the conclusion or decision making

Thanks Chris..


Better/faster to blend the data and build a nice model in alteryx and the push via tde file to tableau to visually analyse.

This is great. I work with a bung of engineers and no matter how I try to show them the data I always seem to get "could I just get this as a table" or "could you make a flow chart." Reminding other that there can be more insight to be gained through visuals analysis is a constant battle, but one worth fighting.

The answer is always in the data. Visualizing it through a graph or chart or table (or dashboard) allows you to communicate the insight gained more easily. The type of visualization you choose depends on which one is the best method of representing the data - distribution, trend, aggregate.

Cannot agree more. I used to write SQLs to explore the data in an Oracle table. Now I use Tableau instead, which is much easier and more efficient because of drag&drop and visualization. At the same time, big challenges still remains because most of our clients are used to Excel and always thinking in the old way. I would rather people tell me what their business problems are or what business issues they want to tackle, and then through the rest to me. I will take care of the data research, data construction and dashboard design (including content and format/layout)., as well as end-user communication. But the real world is not always ideal and perfect.

Subscribe to our blog