Tableau Enterprise Reviews

Bob Dylan – folk hero to thousands if not millions  – caused a furor when he appeared at the 1965 Newport Folk Festival with … an electric guitar!

If you read about the incident you’ll discover that there was a mammoth sense of betrayal within the folk-centric fold.  How could their hero embrace rock music?

I thought about this musical misstep / milestone when I first read Stephen Few’s rant over Tableau “veering from the path” for allowing two unworthy visualization types and one unworthy visualization implementation to sully Tableau’s latest release (see http://www.perceptualedge.com/blog/?p=1532).

Ironically, I was saddened and disappointed — betrayed is too strong a word — by Few himself over his recent dashboard design competition (see http://www.datarevelations.com/stephen-fews-dashboard-design-competition.html).  But let’s not dwell on that just now.

With respect to Tableau 8, While Few acknowledges that “this version of the software includes many worthwhile and well-designed features” he maintains that Tableau’s introduction of visualization types that are “analytically impoverished” is an indication that the company’s “vision has become blurred.”

This is a grossly unfair assessment as while there may be some aspects to the release that leave me shaking my head, the vast majority of features show crystal-clear vision and laser-guided direction.

Indeed, as someone who uses Tableau every day of every week, I think version 8 is a godsend as the productivity improvements for me, my clients, and my students will be huge. Yes, there are some things in the product that are half-baked – and goodness knows we’re not used to seeing anything half-baked from Tableau.  But for Few to write 6,000-plus words condemning the release while barely acknowledging the incredible advancements seems grossly unjustified.

So, let’s plug in the 1965 Fender Stratocaster and have a listen, shall we?

Acknowledging that which is Half Baked

I’ll start off by acknowledging some of the things that I think are half-baked:

• Bubble charts have an algorithm flaw, and size and placement cannot be controlled
• Forecasting is under-documented and does not inspire confidence
• Treemaps are flawed
• Multiple Value (Dropdown) filters needs an “apply” button

Bubble Charts

I have no problem with Tableau including this chart type, even though I don’t know if I will every use this viz type in a production environment.

I might, however, use this to help me get a visceral feel for the data.  That is, I rather like the “gestalt” appreciation I get from looking at a bubble chart.

My two problems with Tableau’s implementation is that it’s too much of a “black box” (i.e., I cannot control size and placement) and that you run into bubble sizing problems if you attempt to display both very large and very small values.

Consider the visualization below that I created for my recent “Infographics Behaving Badly” post.

* A visually-compelling, but analytically-flawed bubble chart. *

As Joe Mako noted, the bubble for The Diary of Anne Frank is the same size as the bubble for The Lord of The Rings even though sales of the latter are almost four times greater than the former.

Apparently, the smallest bubble Tableau will draw is 1/25^th the size of the largest bubble.  Rumor has it that this shortcoming will be addressed in a forthcoming bug fix release.

Forecasting

I’ve spent several hours experimenting with this feature and I’ve come to the conclusion that I’m better off creating the forecast using an algorithm that I can control.

Don’t’ get me wrong, I would love to be wrong about this and find out that this feature is deep and rich, but based on my experience it smacks of first iteration, “good-enough-to-get-a-check-mark-on-a-comparison-chart” quality.

* Default forecasting results do not inspire a lot of confidence. *

* Results when you take into consideration trend and season. *

Treemaps

Few’s comments on the shortcomings in Treemaps are spot on, I’m just not terribly upset about it as we never had treemaps before.  While the implementation is flawed, it’s still useful.

But yes, I hope Tableau makes this better down the road, as per Few’s recommendations.

Multiple Value (Dropdown) Quick Filter

I’ve wanted this feature for several years as the standard multi-select filters take up A LOT of screen real estate, as shown here.

* A check-all-that-apply quick filter. *

So, I’m delighted that this functionality can now be neatly packed in a compact dropdown list box.

* A compact check-all-that-apply quick filter. *

One problem still persists with check-all-that-apply filters and that is Tableau’s insistence on redrawing the visualization after every click.  For some projects it can take several seconds for Tableau to re-render the viz.  Users lose patience with this type of behavior.

I believe that Tableau did have an Apply button in the works that would have addressed this problem but they ran into some stability issues and elected to postpone implementing this feature.

I hope to see it soon.

What About Word Clouds?

I don’t mind that Tableau gives people a way to create these things even though I think they are an analytically-flawed way to present information (although they can pack more of an emotional wallop than a bar chart).

A major problem with word clouds occurs when your data contains different terms that describe the same or similar sentiment. Consider the word cloud shown below that shows survey responses to the question “what is your mood right now?”

* Are the majority of people happy? *

One might think that most respondents were happy, but look what happens if we “linguistically normalize” the terms that are synonyms of “sad”:

* … or are more people sad than happy? *

It turns out that more people are in fact sad.

Note: There are products that are capable of parsing full sentences and are able to “disambiguate” and then normalize terms under umbrella concepts (although I have yet to see the functionality in any word cloud generators).

Acknowledging that which is Fully Baked

I could probably write 6,000-plus words on all the new features that wow me in version 8, but I’ll just focus on five that will allow me to produce better work faster:

• Applying filters to selected sheets (this is just brilliant)
• Enhanced set functionality
• Floating / free-form dashboard elements
• Enhanced marks card (and in particular multiple text entries)
• Improved data blending
• Bonus item – Tableau’s incredible responsiveness during the beta

Applying Filters to Selected Sheets

I’ve been pining for this since version 4 and while it has taken Tableau more years than I would have liked to see this realized, the implementation is beautifully rendered.

Tableau exceeded my expectations here as in making my case for this feature I just wanted to see the following three filter options available to me:

• All worksheets in the workbook
• Just this worksheet
• All worksheets in this dashboard

But as with so many other beautifully-crafted features in the product (including the “add reference lines” dialog box, which one needs to implement Few’s own bullet charts), Tableau developed a more generalized and elegant approach for controlling filter scope, as seen in the following menu sequence and dialog box.

*Start by indicating you want to control the scope…*

*… then apply the filter to selected sheets.*

Do you hear that? That’s a choir of imaginary angels singing “ahhhhhh”.

Enhanced Set functionality

The new IN / OUT set functionality is a huge addition and the ability to combine sets is beautifully rendered as shown in this dialog box.

*Holy Venn diagram, Batman!*

Work like this is hardly an indication of blurred vision.

Floating / free-form dashboard elements

With past versions of Tableau I’ve spent a lot of time fighting with Tableau’s dashboard layout constraints. Indeed, I would spend hours sparring with Tableau to place visualizations, quick filters, legends, and so on, into a too-cramped-for-all-the-elements-I-want space.

With the latest release there will be a lot less fighting as any and all objects can now be floating elements, so I can easily place objects on top of other objects.

While this may not seem like a big deal, the ability to place legends and filters atop a visualization (vs. locking these items into a designated corner) makes for more efficient use of space and a much slicker looking dashboard.

*In this example, floating elements buy me 80 to 100 pixels.*

Here’s how I would have presented this in the previous release:

*Having to put filters and legends in a designated area means less room for the visualization itself.*

Enhanced marks card (and in particular multiple text entries)

I never had a problem with tableau’s “shelf” concept for controlling text, color, size, and so on, but the new “button” concept and attendant marks card implementation are well-designed and will make my life easier, both as a developer and as someone that trains others.

*Tableau’s new marks card.*

But there’s more to this than just a slicker user interface.  By moving away from the one-item-at-a-time-on-a-shelf approach you can now have multiple items controlling facets of the visualization.  Having multiple text items in play is particularly useful, as shown here.

*It’s now a snap to display both count and percentage by placing multiple text elements on the text marks card. I’m also using the floating elements feature to put the title and explanatory text within the viz itself.*

Improved data blending

There are a handful of technologies that never cease to amaze me.

WiFi certainly falls into this category.  Even though I’ve used it thousands of times, I’m always enthralled that I can be sitting in a coffee shop, airport lounge, or family room and I can connect to the Internet.

I have the same reaction to trade show pop-up display booths.  I’ve set these things up dozens of times and I’m blown away every time I see the little compact frame expand to ten times its packed size.

I have the same reaction tor Tableau’s data blending capability.  That I can easily – and I mean really easily – get data from one source (e.g., SQL server) to play nicely with data from another source (e.g., Microsoft Excel) without having to think very hard never fails to amaze me.

There had been a major shortcoming in previous releases and that was that the field that linked the two sources had to “be in play”; i.e., either the field was visible or it had to be placed on the level of detail shelf.

This is no longer the case with Tableau 8 so this capability that was so amazing in previous versions is now even more amazing.

Bonus item – Tableau’s incredible responsiveness during the beta

I’ll confess that I thought the various beta builds for version 8 were quite buggy – significantly buggier than with previous versions of Tableau. To be fair, betas from previous releases were insanely stable and beta builds in V8 were no buggier than betas from companies like Microsoft.

Still, having worked with betas going back to 2006, I wasn’t used to stuff not working right.

But I never had much time to worry as Tableaus responsiveness to my bug reports allayed all my fears.  Indeed, their rapid response and genuine concern for my concerns showed great customer focus.

Particular praise should go to Francois Ajenstat whose attentiveness was second-to-none. Our community is lucky to have him as such a stalwart user advocate.

Parting thoughts

While I disagree with the one-sidedness of Few’s critique, I’m profoundly grateful that he did express his dismay as  given his reputation – well deserved, I might add – I suspect we’ll see Tableau attend to the itemized shortcomings sooner rather than later.

Also, it is posts like Few’s – and the attendant replies and follow-up posts, including this one – that produce better products and services.  Indeed, it is through this open discussion that we spread our collective knowledge and expertise, and improve the state of the art.

Let’s keep the passion going..

Thoughts on Standard Business Practices, User Expectations, Tableau’s Server Pricing Model, and Appealing to the Consumer’s Inner Narcissist.

In my six-plus years of using Tableau I’ve created hundreds of dashboards and thousands of interactive visualizations.  In observing these creations out in the field I noticed something rather disappointing – the vast majority of people for whom the systems were created were not interacting with these so-called interactive dashboards.

I’ve made a lot of progress in getting people / organizations over this hurdle (see https://www.datarevelations.com/hey-your-tableau-public-viz-is-ugly-and-confusing.html for some thoughts on the matter) but I realize that there is a very stubborn, business-as-usual mentality that is slowing down the adoption of interactive dashboards.

And as much as I love Tableau, I believe the company’s server pricing model is retarding rather than accelerating the adoption of a more enlightened approach to data exploration and sharing.

Let me explain.

Turning something dynamic into something static –
My students’ experiences

In addition to my consultancy I am a Tableau Training Partner.

One of the somewhat sobering – and disheartening – things I hear from my students is that organizations are using Tableau to embed static images in static reports.  That is, while much of the curriculum is spent showing people how to create highly interactive visualizations, the vast majority of attendees report that the way they will share their visualization brilliance is with PDFs and PPTs.

Say what?

You mean your company has invested in Tableau and you’re just going to copy and paste stuff into static documents that get e-mailed?

After a few seconds of sheepish nods all around we usually get into a discussion of why this is happening and what one can do to help organizations embrace the full power in Tableau.  Here are some of the things we discuss:

• Change Management
• User Expectations
• Deployment Hurdles
• Cost (i.e., server pricing)
• Make it Irresistible by Making it Personal

Change Management

A lot of organizations look at Tableau as being a type of report writer, something that is tantamount to using a spreadsheet as a word processor.  As Tableau makes inroads into organizations it seems it has to first prove itself by duplicating whatever functionality it is supposed to replace, rather than complimenting, augmenting, or leapfrogging the incumbent technology.

While Tableau Server can be cajoled into automating the creation and distribution of PDF files, I don’t think this is a great use for the product.  Indeed, if you need different cuts of the data or different pre-filtered views for different personnel – but you want to distribute these as static reports – Tableau is not, in my opinion, your best bet.

So, for those of you in the avant garde of your organizations, you need to manage expectations of your colleagues and higher-ups and explain that Tableau is not a report writer.

User Expectations

I’ve already written quite a bit about this (see the “Usability” portion of https://www.datarevelations.com/hey-your-tableau-public-viz-is-ugly-and-confusing.html) but you just can’t expect people to “get” your dashboards without at least a little instruction and training, especially if you use visual filters.

I’ve brokered a couple of lively debates around visual filters and how long it will be before people just expect clicking a chart to have some impact on a dashboard.  For example, if you have a dashboard that has quick filters like the ones shown below, most people will know what these things are and how to work with them.

Figure 1 — Tableau quick filters. People know what these things are and how they work.

However, if you were to expose these same people to the dashboard snippet shown below,very few will know that clicking a portion of one chart will trigger an action that filters all the other charts in the dashboard.

Figure 2 — Visual filters. Without instruction people will not know that selecting a bar or bars will filter by the selection.

This is amazingly potent stuff, but unless you show people how it works they aren’t going to simply discover it on their own.

So, how long will it be before people “know” that charts can be filters, too, and this becomes expected functionality?

Based on nothing more than gut, I predict it will take three years, but I wonder what Tableau could do to accelerate this expectation.

And as I wonder, I find myself thinking about Tableau Reader and Tableau’s Server licensing model.

Deployment Hurdles with Tableau Reader

I’m very grateful that Tableau offers a no-cost reader.  The problem is that Tableau Reader is a non-starter with many organizations and potential individual interactors for myriad reasons:

1. You lose a lot of people when you ask them to first download and install something.
2. Those that you don’t lose may not be able to download and install the reader (e.g., it is not an “approved” app in the organization).
3. There is no way to protect the underlying data from prying eyes or to even password protect a packaged workbook.
4. You cannot customize the workbook for different consumers of the data (e.g., have certain things pre-filtered based on department, job function, etc.)
5. You cannot easily add helpful scaffolding to the dashboards that walk people through how to use the dashboard (whereas you can do this when you embed a dashboard inside a web page).

So, what about Tableau Server?

Tableau Server Pricing

Tableau Server is a great solution, but it can be prohibitively expensive.

The last time I investigated, there were two ways to purchase Tableau Server:

• An individual interactor licensing model that costs $1,000 per license with a minimum of 10 licenses; and,
• An “all-you-can-eat” core licensing model that costs between $160K and $250K, depending on whether you purchase a quad-core or eight-core license.

The first license is very reasonably priced if you have a small group of people that will be interacting with Tableau frequently, and the second license is very reasonably priced if you have a large group that will be interacting frequently.

But what happens when you have a large group of people that wants to make light use of Tableau?  That is, what if you have thousands of users but each of these users will only need to interact with Tableau three or four times a year, for maybe 30 minutes at each session?

I have had four different clients that have fit that very scenario – thousands of potential interactors but very few concurrent interactors – and they would love to implement a Tableau server solution but the $1,000 per user or $160K core license is totally untenable.

I understand that Tableau does not want to undervalue its technology, but why not offer a concurrent licensing model?  That is, make it so that the server can only handle a certain number of concurrent users at one time.  There are so many reasons why this would make sense for both the organizations that want to adopt the technology and for Tableau:

1)      The initial cost to adopt will be low as one could purchase a five or ten-user concurrent license.

2)      Many people in the organization will be able to “kick the tires”

3)      As people see the benefits of this approach, more and more people will use it more and more often.

4)      This in turn will lead to organizations purchasing more concurrent licenses.

Make It Irresistible; Make it Personal

Let’s say we surmount the training and cost issues.  Will people in fact dig in and click?

I’ve learned a lot by observing how people use – or do not use – the dashboards I’ve created.  To get people to use the dashboards they have to care about the data and people will care deeply if the data is about them.  That is, the dashboards that get the most traction answer questions like these:

• How is our company doing vs. other companies?
• How is my department doing vs. other departments?
• Where do I stand vs. my peers?

Consider the example below that shows a simplified version of a CTO compensation dashboard I created earlier this year.  A person can apply various filters and see salary ranges based on the filter settings.

Figure 3 — Generalized salary visualization.

Now, compare this with the visualization below where we allow the user to enter his / her salary, and then apply the filters.  We get a much more compelling story and we make it a lot easier to see how the person is doing vs. others.

Figure 4 — Personalized salary visualization.

This type of dashboard – where we have both an interesting story and we incorporate data about the person viewing it – will generate a lot of interest and once people see how powerful and personally meaningful this is they won’t want to go back to PDFs and PPTs.

And they will click.  Often.

What is most valuable?

How has it helped my organization?

What needs improvement?

For how long have I used the solution?

What was my experience with deployment of the solution?

What do I think about the stability of the solution?

What do I think about the scalability of the solution?

How are customer service and technical support?

Which solution did I use previously and why did I switch?

How was the initial setup?

What about the implementation team?

What's my experience with pricing, setup cost, and licensing?

Which other solutions did I evaluate?

What other advice do I have?

1.1 General

This document compares two BI tool players in the Big Data arena – Tableau (http://www.tableausoftware.com/) and BIME (http://www.bimeanalytics.com/).

1.2 Comparison: BIME vs. Tableau

1.1 Summary

Significant strengths of Tableau:

• Financial stability, market presence and track-record (both WW and in IL)
• Tableau's license costs are not cheap, but seem cheaper than BIME's in the long-term
• Israel presence – support and professional services

Significant strengths of BIME:

• Cloud offering – BIME is a SaaS product, thus cloud-enabled top to bottom.
• While Tableau does have some capabilities in this domain, it's not a true cloud solution.

Significant strengths of both:

Visualization, user capabilities (Ad-Hoc, Analytics, etc.) and Ease-of-implementation.

Significant weaknesses of both:

API capabilities are quite limited and immature.

Note:

1. It seems like an issue both vendors are aware of and are working on in their roadmaps.
2. It is not the most important feature, unless you plan an embedded/OEM solution.

Performance –

Both tools have a native connector to almost every Big Data platform available on the market. While this does not ensure good performance, it does improve the chances of getting better performance than other tools, which do not have such a connector.

Tableau is charting, graphing and data analysis with go-faster stripes. It has obvious appeal, with prolific amounts of eye-candy and a relatively easy to use interface. As with other products of this nature its utility is firmly anchored in visual exploration of data using every format imaginable. It is not a data mining tool or a text analytics tool, but sits in the traditional business intelligence camp, albeit with a rich visual interface. It is positioned as one of a new breed of BI tools designed to deliver pervasive BI capability throughout the organization, or at least to those who need such tools.

The entry level product is Tableau Public, available as a throttled down free version, or in a Premium version with fewer restrictions. It is primarily targeted at the creation of graphics for web sites and offers a ‘paint-by-numbers’ approach to the creation and publishing of such graphics. A rich set of formats are supported including bar and line charts, heat maps, bubble charts, geo maps and many others (you are spoiled for choice really). Graphics are updated automatically when the underlying data is modified and links can be made to other content on a web site. The Premium version supports larger data sets and the optional suppression of access to the underlying data set. There are numerous web services of this nature (Jolicharts for example), but Tableau Public is certainly one of the best free offerings.

Tableau Desktop supports the visualization of data on the desktop and connects to a bewildering array of data sources, either individually or in concert. The Tableau Data Engine sits on a PC and calls upon the relevant data sources when needed. It executes queries in-memory for speed and switches data in and out of memory automatically, although clearly some wisdom is needed when accessing live data sources.VizQL is Tableau’s Visual Query Language and is claimed to bypass the usual extraction, format, graphing process to build a direct link between data sources and visual representations.

Tableau Server supports browser based tools for data visualization and as such opens BI up to a very wide audience. It provides the very wide range of visualizations and dashboards supported by Tableau, and also make them available on portable devices (iPad and Android).

Tableau places great emphasis on the ability to create visualizations without the need for any technical skills (scripting). Provided Tableau always offers what you need this is fine, the moment you want something different this could be problematical. For this reason I think it is wiser to have both options – scripting free visualizations for run-of-the mill tasks, but scripting capability for more unusual needs. Other offerings are stronger in this respect.

Most users love Excel, non-users hate it. When it comes to data visualization, Excel is generally dispised, except by those that have to make dozens of charts every single day. I call this the Excel Stockolm Syndrome. These are the forsaken data visualization users that keep making 3D pies when they should know better by now. Tired and overwhelmed. Not in the mood the learn yet another tool just to make those elusive “effective charts”. If you link good visualization to a tool they have no access to, you can be sure that the whole message is lost.

Becoming a Data Visualization Anarchist

I think things can be changed from the inside, improving the way people use Excel. I write for Excel users because I’m one of them. That’s not going to change soon. But I love data visualization, not the tools that make it happen. I specially like interaction, multiple charts and making them available on the web. And I need to manage more data (not big data, just more data). Some things can’t be done in Excel or require too much effort.

The Portuguese poet Fernando Pessoa has a funny short story called The Anarchist Banker. The idea is that only a banker can be a true anarchist, because only a banker can be free from “social fictions”, specially money… In data visualization, this means getting the tools out of the way, by learning them or avoiding them.

I chose the learning path and I’m learning R now. I always wanted to make those scatterplot matrices. And I want to play with the ggplot2 package. A programming language is covered but R is not going to pay the bills.

Enter Tableau and Qlikview

I will not complicate matters  by discussing how I chose Tableau and Qlikview and not Spotfire, for example. I just want to choose one. Qlikview vs Tableau. Comparison articles like this and this are very helpful, but a man is a man with his circumstances. Each starting point is different from everyone else. Let me tell you what I think I know about these tools in this early stage.

Tableau

I like Tableau, I have to admit it. I like the fact that you don’t have to fight stupid defaults in design and formatting, because I share the same data visualization principles.

I like its enthusiastic and knowledgeable community. Let me give you two simple examples. I spent a lot of time making this horizon chart in Excel, and Joe Mako quickly came up with a better version in Tableau.

Then I tried to be creative with the bamboo charts and Joe Mako strikes again, with a better implementation. I’m starting to get nervous… (kidding)

I know and respect many Tableau users, not because of Tableau but because I share the same views regarding data visualization.

Apparently, maps in Tableau are good enough, so that’s a good point.

And as a blogger, I want to make my work available to the web, and Tableau Public is a nice option (my population pyramid).

The Guardian often publishes Tableau visualizations. I’d like to try that with the local newspapers here.

On the other hand, we know how stubborn some datavis experts are. Is Tableau that stubborn? Can clear vision and the right principles become a straitjacket? I really hate straitjackets (“the idea of”, never actually tried one…)

In my country, Tableau is virtually unknown and I am not sure if I want to sell shoes in Africa.

Qlikview

I know even less about Qlikview. The first chart I see in its video is the  pie chart above. Not exactly a shiny example of good data visualization principles.

Apparently there is a very active Qlikview community on Linkedin but not so much on Twitter. Probably this is meaningful.

I keep reading that Qlikview is better than Tableau when it comes to making dashboards, while you should explore the data with Tableau. It’s a good point in favor of Qlikview (that’s what I need now). Extensions and the market seem to be interesting too.

Qlikview has several business partners here. Actually, I was invited to work in some Qlikview projects in 2013 (obviously I have to learn the basics until then). They can pay a lot of bills.

Its not always about features

Not everything is black and white, not everything can be decided based on feature-by-feature comparison. Not everything is heart, not everything is reason. If I choose Tableau, my data visualization skills will improve a lot. Qlikview is harder to predict. I’m sure there are many users that dislike the pie above. If not, Qlikview can be more, hummm, challenging.

What I’m going to do

I mentioned those Qlikview projects, but I’ll try to remove them from the equation, at least for now.

I have a simple dashboard in Excel and I’d like to create Tableau and Qlikview versions. That’s probably one best ways to evaluate a tool, using my own work.

So, can you help me?

I’d love to learn from you. Can you answer questions like:

• How do they compare regarding maps? Is it simple to add your own maps?
• Is it true that it’s easier to make a a centrally designed dashboard in Qlikview, while Tableau has a more exploratory nature?
• How can I share a Qlikview chart in my blog?

And please don’t tell me I have to learn both…