Darya Efimova is a Digital Transformation Observer at Iflexion.
Has your organization decided to adopt and implement the Tableau BI platform, namely its Tableau Server and Tableau Online versions?
If so, you won’t need anyone to tell you that it’s a) expensive to scale, and b) an eminently capable enterprise analytics tool.
That’s why you won’t find those or similar commonly quoted facts discussed in this brief guide for businesses new to Tableau. Instead, you can pick up five useful insights that will help you avoid falling victim to implementation and adoption hiccups as you deploy and scale your Tableau solution.
If your organization is going to spend the sums required for a Tableau Server or Tableau Online deployment, you’ll want to be able to get the best from the software. Tableau allows you to build out high-performance BI dashboards and to plug in multiple applications such as CRM or ERP. However, its performance, as with any business information system, still depends on the quality of the data that you feed into it.
Of course, data cleansing should be a regular and standard process in the maintenance of your business IT environment. Whether it is or not though, you will do well to include a data preparation phase in your Tableau implementation plan.
Fortunately, Tableau itself now offers a product that you can use to clean and prepare your data before creating visualizations. Tableau Prep launched in 2018, to simplify data preparation not only for the deployment of Tableau, but, just as importantly, for its everyday use. Without the need for a separate ETL tool, Tableau data preparation will be within reach of your business users as well as dedicated analysts.
Speaking of analysts, do you already have some in your team that are familiar with the latest visual approaches to data presentation?
If not, you may need to factor some training and support into your Tableau deployment plans. While the need for training business users may be obvious, it’s easy to forget that many analysts are not conversant with the modeling and design requirements of a visualization tool.
Storytelling and strong visual design skills are the most valuable disciplines for Tableau authors. Are those qualities lacking in your analytics teams?
If so, you may wish to consider upskilling initiatives, which could be as simple as providing analysts with books by visualization gurus like Stephen Few and Edward Tufte. For more comprehensive training and development, your organization could consider online data design courses or turn to Tableau consulting.
You know that Tableau is a tool exclusively designed to provide data visualization, but do all your prospective users know that too?
A common mistake among new Tableau users is to expect that they can use it to:
These are things to look out for after deploying Tableau in your organization. If your users try to apply it in the ways described above, they will not be playing to the tool’s strengths. The resulting issues can range from mildly frustrating to downright exasperating.
These issues are counterproductive at the best of times, but especially so immediately following the deployment. Not only will your team be less productive, and your visualizations less than inspiring, but the frustrations will create inertia in your efforts to reach full adoption across your organization.
Focus on the Outcomes You Want, Not Those You Had
Thorough training and clarification of Tableau’s capabilities will be critical if you wish to avoid the problems mentioned above. Impress upon your team the need to treat Tableau as a completely new way to answer business questions.
Forget replicating what you already have. Instead, look at an existing report, determine what its purpose is, list the questions it should answer, and have your team design it from scratch using Tableau’s core capabilities.
That will allow users to grasp the software more completely and gain satisfaction from its use. You might even find the resulting visualizations can answer more questions than the reports they supersede.
There are a couple of ways to connect your database tables to Tableau, one of which involves using the multiple table storage option. Many organizations will want to connect several tables at once, and it would seem intuitive that this Tableau facility would be the best way to do so. However, that’s not necessarily the case.
If your users wish to use the multiple table option, they shouldn’t assume it will be fine to connect all the tables simultaneously. It’s a sure way to run into problems with record duplication, leading to poor performance or inaccurate results.
Instead, a step-by-step approach will yield better outcomes. Connect the first table and check the results. Then bring one or two more tables into the query and check again. If the number of records seems excessive, change tack and use a separate connection for each table, then apply Tableau’s blending functionality to combine them.
While the multiple table option is useful under certain circumstances, even the current guidance from Tableau itself recommends an experimental approach. If in doubt, it will make sense to default to single table storage.
If you deploy Tableau Server (and many organizations do), the last thing you want is your expensive investment becoming a dumping ground for obsolete content and duplicated data. A little time and human capital invested in monitoring and organizing the server environment will pay off and help you maintain performance—as well as usability.
The good news is that Tableau has an integrated site status monitor to help your administrators keep on top of server management. A best practice would be to sift through the workbooks housed in the server regularly, and isolate those which are rarely used or no longer of value. After a few months, these can be deleted, saving space and keeping the environment clean and simple for users to browse.
Tableau is one of the most powerful tools currently available for data visualization, and in a desktop scenario it is relatively straightforward to set up and use. However, as with most freshly implemented applications, awareness of its characteristics, strengths and weaknesses is essential to prevent growing pains from turning into stumbling blocks.
When implementing Tableau at scale, it makes sense to pay attention to the five possible pain points described in this guide, and cultivate awareness of them throughout your organization. By doing so, you should enjoy a smooth and successful roll-out of Tableau, without significant performance problems or adoption barriers.
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