I had the chance to get to Tableau Customer Conference in early November 2012 and thanks to exceptionally good organization of the event I was able to greatly enhance my picture of Tableau (which I first reviewed 2 years ago) and get answers to some questions.
Below are my impressions from Tableau (which I haven't used in real projects yet) in comparison with QlikView -- tool I've been working with since 2009.
First thing I'd like to tell -- starting from version 8 Tableau can honestly be considered a truly mature product -- a big difference with what I saw two years ago. It's a smartly designed, feature-full and powerful analytic tool which is especially good for ad hoc query and analysis (Q&A). Prior to Tableau I considered BusinessObjects WebIntelligence to be the best Q&A tool on the market. However, in my picture of BI world this honorable title now belongs to Tableau.
Here is what I liked (not in order of importance):
State-of-art data visualization makes Tableau outstanding in the crowd of BI suites. Tableau people talk about "being creative with data" and it's easy to believe in this while looking at clean and elegant Tableau dashboards. By the way, in French tableau has two meanings -- painting and table. Artwork and data. Excellent match of brand and product concept.
Drag-n-drop authoring as cornerstone of analysis and design processes. That's what WebIntelligence was good at, but Tableau makes it even better, simpler and easier. Sadly QlikView has almost nothing to offer here -- fields still have to be picked from a cluttered properties dialogs and dashboards have rather static layout.
In Tableau there are (at least) two special types of dimensions: time and location. I like the idea of special dimensions in general because indeed some dimensions should be treated differently for more efficient analysis and Tableau demonstrates this very well. For instance location dimensions can easily be used for maps and spatial analysis. Time dimensions should be treated differently as well because almost in all cases information is relevant only in specific time context.
Maps is one of the strongest features in Tableau. Usually maps is a real pain for BI developers because support for maps usually is rather poor in BI platforms. Some of them provide mapping functionality via integration with 3rd party GIS platforms like ESRI or MapInfo. But level of integration is never good enough, not to forget additional licensing costs. Some (e.g. QlikView) imitate mapping by offering maps simply as a colorful background for scatter charts, without important capability of highlighting regions or providing additional visual layers. Tableau has done a good work here and offers excellent mapping functionality which includes regularly updated maps and complimentary information (e.g. population or income) licensed from 3rd parties (without any additional costs for customers).
Groups and Sets. Ability to dynamically group dimensions is not something unseen before in BI suites (e.g. in Cognos). However, creating naming sets on the fly, applying set algebra operations (introduced in Tableau 8) to them like addition, intersection, subtraction and calculating aggregates against sets is a very useful and practical feature, for some reason underestimated and neglected by major BI vendors. I can recall only BusinessObjects Set Analysis which was quite clumsy last time when I saw it a few years ago.
QlikView has not much to offer here. While it is possible to save different selections into bookmarks it's not possible to apply set algebra to them. Comparison of aggregates of two ad hoc sets is possible but requires knowing rather complex set analysis expression syntax which is a non-trivial task for even advanced business users. How many of them are capable to quickly write something like this?
sum({Set1<Year=$::Year, Month=$::Month>} [Amount]) - sum({Set2<Year=$::Year, Month=$::Month>} [Amount])
Despite developers of a QlikView application can implement comparison of sets in a dashboard, it's not available out of the box. Dynamic grouping (of dimensions) is not possible in QlikView at all -- grouping requires creating additional data structures and reloading the application.
Now let's talk about some disadvantages of Tableau.
Performance. Working with QlikView it's easy to forget what performance optimization is. Surely, there are some tricks how to improve performance for very large datasets (hundreds of millions of records) but this question rarely appears in daily agenda of a QlikView developer. Having subsecond response time on 20 millions of records even on a laptop is not something unusual. However, I suspect that question of performance optimization will rise much more often for Tableau applications which heavily rely on relational databases. And that's not so trivial task as it may seem.
SQL query optimization is not a trivial task itself and may include special indexing strategy, joins optimization strategy and use of various hints and tricks -- task that requires experienced database professionals and is simply impossible for a business user (who has a lot of other things to do besides query optimization).
However that wouldn't be so dramatic if that was the only thing to do. Tableau enhances source data with its own data (e.g. calculated fields, dynamic groups, sets, latitude and longitude for locations) and also makes in-memory cross-source joins. Therefore query optimization requires good understanding of how Tableau performs these operations under the hood, how it interacts with database and what are implications of different settings. This makes task of performance optimization even less trivial.
I've got impression that performance is not something that Tableau is ready to boast about. Calculation in-memory engine is much weaker and far not so sophisticated as QlikView's one. Not significant but interesting detail -- two demo databases in standard Tableau desktop installation have only 4'248 and 8'399 records respectively.
One more reason for concern is that both Tableau Desktop and Tableau Server exist only in 32-bit version. We were told that 64-bit version is being actively developed however as of now the only version available for customers is 32-bit.
Having in mind these concerns about performance I'm not sure that ability to directly work with very large datasets really becomes an advantage on practice. Yes, theoretically it's better to be able to query 10TB of data than not to be. But would it have any practical use if this could require a few hours of waiting time?
Advanced authoring. Contrary to QlikView, Tableau makes bet not on syntax and scripting but on various settings and actions performed via user interface. While it is good for fast start and early learning curve, as complexity of dashboards increases it eventually leads to necessity of knowing various hacks, tricks and workarounds. For instance making objects (charts, tables, text labels) appear or disappear depending on some parameter (variable) is a straight forward task in QlikView but is actually a hack in Tableau. And that's not good, because in case of QlikView there is albeit complex but logical and well documented syntax but in case of Tableau you will need to learn these hacks and tricks from someone else. Because sometimes it's near to impossible to understand logic behind them without help of more experienced developer. So finally experience of a user becomes largely defined by amount of various collected hints and trick.
Use of screen estate. It's hard to compete with QlikView in efficiency of screen estate use. QlikView offers various gadgets, in-line minicharts, easy management of object visibility which allows making dashboards very information rich. While it's a usual thing for a QlikView dashboard to have 10 listboxes, having 10 quick filters (analogue of listbox) on Tableau dashboard will most probably make it completely cluttered and barely usable. Also such thing as in-line minicharts simply doesn't exist in Tableau.
Need for an ETL. As any other BI tool that heavily relies on database engine Tableau needs cleansed and transformed data. In general this also is true for QlikView. However since loading script in QlikView is capable to perform light ETL and data cleansing therefore in many cases this is sufficient enough.
Lack of collaboration activities -- while I'm not quite excited about the way data annotation is done in QlikView (here is my point of view on data annotation) however it's present at least in this form and instant application sharing is simply awesome feature Tableau definitely needs something that would allow users discuss and share their findings.
Lack of collaboration activities -- while I'm not quite excited about the way data annotation is done in QlikView (here is my point of view on data annotation) however it's present at least in this form and instant application sharing is simply awesome feature Tableau definitely needs something that would allow users discuss and share their findings.
Resume
Tableau is an excellent Q&A tool which is very well designed and suited for non-technical users. It is powerful, easy to use, highly visual and aesthetically pleasant. Good evidence that Tableau is a good fit for business users was audience of TCC2012 -- there were a lot of women and at the same time there were not many Indian developers which is not a typical case for a BI event.
However, promise of Tableau's execs and sales that "IT is not required with Tableau" is much less true than it might seem because involvement of IT personnel could be higher than expected as more complex dashboards become required.
QlikView applications usually require IT developers to create them, however the developers get much more flexible and powerful toolkit that allows them to create very information rich dashboards with fixed layout.
As vendor, Tableau is clearly on rise and the company seems healthy. Their product is developing rapidly, which unfortunately is not the case with QlikView -- I'm getting impression that QlikTech chronically under-invest in R&D and put too much on sales and marketing. There are lots of things in QlikView which wait to be modernized and improved very long time. However, its main killer feature -- ultra-fast in-memory engine -- is still unbeatable.
UPDATE (7/31/2015)
Since the time when this post was published Tableau has got a 64-bit version and greatly improved performance. Also, the data manipulation part now is less critical for Tableau with the help of EasyMorph (http://easymorph.com) -- an easy-to-use visual data transformation tool for non-technical users created by the author of this blog.
Qlik in turn released QlikSense 2.0 which now is the company's flagship product. It has drag-n-drop dashbord authoring, redesigned security system and even faster in-memory engine. But the most interesting part of it is its highly customizable layout plug-in architecture that makes possible to insert literally any visualization into a dashboard.
UPDATE (7/31/2015)
Since the time when this post was published Tableau has got a 64-bit version and greatly improved performance. Also, the data manipulation part now is less critical for Tableau with the help of EasyMorph (http://easymorph.com) -- an easy-to-use visual data transformation tool for non-technical users created by the author of this blog.
Qlik in turn released QlikSense 2.0 which now is the company's flagship product. It has drag-n-drop dashbord authoring, redesigned security system and even faster in-memory engine. But the most interesting part of it is its highly customizable layout plug-in architecture that makes possible to insert literally any visualization into a dashboard.
