Tableau vs. Power Pivot Part 2: Basic Charting

Today, we will talk about creating basic charts in Tableau and Power Pivot.  To be specific, Power Pivot cannot create charts.  In order to create charts out of Power Pivot, you must either use Excel or Power View.  We will examine both of these as options.  As usual, we will use the Superstore Sales sample data set from Tableau.

Bar Graph (1 measure by 1 dimension)

The bar graph is most common of chart types and is useful for almost any type of analysis.  So, let's look at Profit by Region.

Profit by Region (Bar) (Excel)

This wasn't too hard in Excel.  However, it required us to first create the pivot table, then create the chart.  The labels and axes are also somewhat lacking.  More effort would have to be put into this to make it presentable.  Let's see how Power View fares.

Profit by Region (Bar) (Power View)

This was much easier than Excel.  The drag-and-drop interface makes everything much easier.  Also, the labels are very intuitive.  The graph is more aesthetically pleasing as well.  The only issue was that I had to resize the chart to see it all.  Finally, let's check out Tableau.

Profit by Region (Bar) (Tableau)

This was even easier than Power View.  I created this graph in two clicks, compared to four in Power View and much more in Excel.  I would say the aesthetics between Tableau and Power View are about equal.  This is the power behind these two tools after all.  It seems that Tableau has edged this one out ever so slightly.

Winner: Tableau

Bar Graph (1 measure by 2 dimensions)

Due to their interpretability, let's stay with bar graphs.  However, let's crank it up a notch and add a second dimension.  Let's see what Profit by Region and Category gives us.

Profit by Region and Category (Bar) (Excel)

Again, this wasn't too difficult.  Excel chose the roles intuitively, putting Region on the Rows and Category on the Colors.  This still required us to create the pivot table independent of the chart.  Also, we're still not impressed with the aesthetics or labels of the chart.  Finally, the label for the colors doesn't automatically appear, which could lead to confusion.  Let's see what Power View offers.

Profit by Region and Category (Bar) (Power View)

Just like last time, this was just a couple of clicks.  The labels and the aesthetics are acceptable.  My only concern about this chart is that the colors are a little too eye-catching for my taste.  A slightly softer palette would be nice in this case.  Now, on to Tableau.

Profit by Region and Category (Bar) (Tableau)

This was actually more complex than Power View.  In Power View, all I had to do was drag Category to the Legend Shelf.  In Tableau, I had to drag it to both the Rows Shelf and the Colors Shelf.  To our knowledge, Tableau is incapable of making clustered bar graphs.  This is probably our biggest frustration with Tableau.  How can a tool that is so good as visualizations lack such a simple feature?  Alas, we digress.  The point is this: not only was this chart more complex to make in Tableau than in Power View, it looks pretty unappealing.  As much as it pains me (a Tableau fanboy) to say it, Power View wins this one pretty convincingly.

Winner: Power View

Scatterplot (2 measures by 2 dimensions)

Now we're getting to the neat stuff.  How well can these tools handle dense graphs?  Let's try plotting Sales and Profit by Region and Customer (A hierarchical relationship!).

Sales and Profit by Region and Customer (Scatterplot) (Excel)

Turns out, Excel can't even do this (at least not simply).  This is all we needed to see.  Moving on to Power View.

Sales and Profit by Region and Customer (Scatterplot) (Power View)

This wasn't a very difficult task in Power View.  We also like the aesthetics of the graph.  All-in-all, this isn't a bad chart.  However, one of our biggest concerns with Power View is that it shows representative samples when the amount of points gets large.  This makes outlier detection nearly impossible.  If there is a way to turn this off, we haven't found it.  This being said, Power View doesn't seem to be a good tool for this type of chart.  Let's see what Tableau offers.

Sales and Profit by Region and Customer (Scatterplot) (Tableau)

This chart was no more difficult to make than the Power View chart.  However, it shows all the points.  Notice all of those outliers in the top-right of the chart?  We were missing most of those in the Power View chart.  Also, this graph just looks slightly cleaner to us.  Looking at this, it's easy to say that Tableau is the winner here.

Winner: Tableau

Mapping (1 measure by 1 geographic dimension)

Mapping is a newer type of technology that is becoming more mainstream.  Let's see how these tools handle it.  We'll try Profit by State.

Profit by State (Map) (Excel)

We couldn't even find a mapping feature in Excel.  If it's there, it's wasn't obvious to us.  Now, let's look at Power View.

Profit by State (Map) (Power View)

This wasn't a complex task in Power View.  However, the points can only be displayed as pie charts, or circles in this case.  Also, the points can only be colored by a dimension, not an automatically discretized measure.  This chart looks nice, but it's difficult to discern too much information from this.  Let's see what Tableau can do.

Profit by State (Map) (Tableau)

It took us three clicks to create this chart.  We think it's fair to say that this chart is much more aesthetically pleasing than the Power View chart.  Also, it's quite easy to discern which states are profitable and which ones aren't.  This is an easy decision.

Winner: Tableau

Summary

Now that we've gone through a few different important chart types, it's become apparent that Tableau is the better choice for basic charting.  We realize that Tableau is not easily capable of creating clustered bar charts, which we find extremely useful.  Perhaps they will introduce this feature in a later version.  Some of you might be screaming "What about Power Map?!?!"  We purposely left it out of this analysis, which is slightly unfair.  We wanted this to be "BASIC" charting.  Power Map, formerly GeoFlow is an extremely cool tool that allows the user to do a large amount of things related to mapping.  In fact, a colleague of ours, Jason Thomas, recently did a really cool webinar and a series of blog posts related to GeoSpatial Analysis in Power Map.  There will be a section later that deals solely with mapping where we will introduce Power Map.  Thanks for reading.  We hope you found this informative.

Brad Llewellyn

Associate Data Analytics Consultant

Mariner, LLC

brad.llewellyn@mariner-usa.com

http://www.linkedin.com/in/bradllewellyn
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