Best Visualization Tool for Dashboards?

More and more organizations are planning and adopting dashboards. And, the question “which visualization tool is the best for dashboarding?” has been asked more frequently. The visualization aspect of BI has been rapidly evolving. There are plenty of vendors and plethora of tools out there. And, they keep on leap-frogging each other and each one has its strong sides and limitations. More than likely, the darlings of today will be forgotten in a few years. So, a quest to find the perfect tool that does it all is likely to fail or it will be short-lived.

I’m not a visualization expert. When it comes to visualizations, I listen to guidance from experts. If you navigate to slide 30 of my “Best Practices for Implementing Enterprise BI Solution”, you’ll see a mockup of a sales dashboard by Stephen Few that is taken from his excellent “Information Dashboard Design” book. This is an example of a pixel-perfect layout with a lot of customizations, such as conditional formatting. No fancy gauges, no bouncing needles, the focus is on intuitive interpretation of data and not on the visualization fluff. If you decide to adopt such visualization standards, you probably already own a great tool for implementing dashboards – SQL Server Reporting Services – which supports bullet graphs, sparklines, as well as a high level of customization.

So, instead of investing in a myriad of tools and hoping that they will solve your BI challenges, my advice would be to spend your money on a solid architecture that would easily allow you to support multiple visualization tools and swap tools as new ones come on board. For example, if you like and decide to adopt Tableau for interactive data visualization and exploration, you’ll find that integrates nicely with SSAS. Here is a dashboard that was done without asking end users to take care of the data logistics and business calculations since this work has already been taken care of in the backend layer. You could also easily implement a similar interactive dashboard with Power View which might not have all visualizations that third-party tools now have but gains in other areas. Please don’t take this dashboard as a best practice, it was meant to only show the possibility of tool integration.


But you don’t have time and budget for beautiful architectures, right? Since you don’t get much help on the IT side of things (if you have IT at all), you want to delegate BI and let Business to take things in their own hands. However, no matter what visualization vendors would tell you, soon or later you’ll find that self-service BI still requires a proper foundation, as Key Unkroth explains nicely in his “Self-Service Business Intelligence Governance” presentation. At minimum, a department would need some sort of data repository that integrates and cleans the data before letting end users in. But if you’ve gone that far, before implementing dashboards, why not add a semantic layer that centralizes business logic and it’s supported by most popular visualization tools out there?


  • So I’ve been working with Tableau and Analysis Services together for the last year or so. Whilst you can get some data out into nice dashboards like this one, the level of functionality when used together is poor. Tableau basically becomes a dumb front end to the cube so many of the features that users love do not work:

    * Calculated fields
    * Custom hierarchies
    * Custom groups
    * Bins
    * Time intelligence is not compatible with cube date dimensions
    * Forecasts

    Also, once you publish workbooks to Tableau server there is no way to flow the user identity back to Analysis Services effectively disabling any cube security you might have.

    The whole point of Tableau is to allow rapid creation and iteration of business intelligence by business users. We have found that it is not possible without a lot of IT involvement when using cubes.

    The solution? Give Tableau users access to the SQL views you use to populate the Analysis Services cube.

    The downside to this is now you have to maintain two semantic models, two sets of security etc. but it is the only way.

  • James,

    Great feedback! Yes, you’ll “loose” SSAS features to matter what self-service BI tool you use. About security, couldn’t you flow the user identity by configuring the Tableau server connection to prompt the user? It’s a pity that their Windows integrated security is not really “integrated”.

    Yes, my experience confirms that data analysts want to have access to raw data. And, as you pointed out, this involves a whole new set of challenges, including data governance, security, etc.

    The real challenge is educating the users what tasks can be completed by connecting to the semantic layer (the most rapid form of BI) and which ones require self-serviced BI models, such as mashing up DW data with external data.

  • Unfortunately not, working with a Tableau consultant we were unable to get it working. Specifically the Prompt User option is not available for cube connections on the server.

    Ideally I’d like them to implement the EffectiveUserName=XXX; argument to the SSAS connection string but I suspect they have no real incentive to since forcing users onto Tableau extract (their own columnstore) makes better business sense for them.