Welcome to part 2 of Biztory’s 2019.3 series! Tableau 2019.3 is out! Exciting times! But what can you expect from it? Last post we tackled the Tableau Server Management add-on from three perspectives: first from a Tableau Iron Viz winnerrr (Timothy Vermeiren, winner of 2018), second from you, the Tableau community, and third from me, a fresh Tableau newbie. This time, we are tackling the well-discussed Explain Data in a similar way. (Did you miss the previous post? Quickly head to it by clicking here)
As mentioned previously, but worth mentioning once more: Tableau 2019.3 seems to be a great grand update as it has a lot of content, for both analysts and server admins. The new features answer questions that have long been asked by the Tableau community, and furthermore, 2019.3 shows thrilling innovations, which may have a tremendous impact on what is to come. Lovely to be part of it all!
Through the different posts, we want to give you the opportunity to navigate to the subjects of your choice.
- As a server administrator, please travel back in time for information on the Tableau Server Management add-on (Yes, you can do that, at Biztory everything is possible, just ask our colleague Hans, we offer outstanding customer support).
- Are you an analyst at heart, excited about Explain Data? Fantastic! You are exactly where you need to be.
- If you are an analyst, administrator, business user/viewer… wait for part 3 for more insights on the Tableau Catalog.
Part 2: Explain Data
What is it? Explain Data offers you the possibility to … well, explain your data. But! It wouldn’t be so well discussed on the Internet if it wasn’t special! Explain Data can make you understand the ‘why’ of your data. For example, did you spot outliers or specific unusual points in your data? Then Tableau gives you possible explanations for them and even calculates which of those are statistically most probable.
Quickly clicking through, Tableau also immediately creates a new sheet/view for you in that regard. Furthermore, Explain Data is free of charge (no, please do NOT attack with your free lunch quote!).
For a more interactive way to understand Explain Data, head to the 1 minute explanation on Youtube.
2 Explain Data, source: Tableau
What does Timothy think about it? Tableau has always engaged in triggering exploration, and with Explain Data, it brings that to a whole new level. The exploration effect becomes that much more powerful and may prelude a strong next step in intuitively exploring your data in the context of self-service analytics, machine learning and data science.
One thing to consider though is that you may not yet become too dependent on this, because understanding what is happening should always be of first priority. The context around your data is very important and you should always keep in mind that correlation does not automatically mean causation. Nevertheless, Explain Data is promising, and we are excited to see what the future will bring for this feature!
What do you think about it? The community is going crazy over Explain Data. People are loving it and feel like they have been given superpowers. Especially being able to add the insight as a new sheet in just one click is received with great enthusiasm.
Qlik and PowerBI already had similar capabilities, so it is good for Tableau to cover that space now. But some people are having doubts on the requirements for Explain Data to work, as there are quite a few (e.g. it only works for single marks, single data sources, aggregated data…) .
For optimal use of the Explain Data functionality, head to the tableau website.
What do I think about? Looking at the comments, I also wondered whether Explain Data has too many requirements. Looking around a bit, it becomes clear that for anyone who has known Tableau for quite some time, the requirements are straightforward, nothing world-shocking, logical even. They know how to easily work around possible problems and carry on.
For users new to Tableau, the situation is different. If you have difficulties grasping dimension vs. measure and aggregated vs. non-aggregated, Explain Data might be less intuitive to you, so maybe if you have a look at those distinctions again, a whole new world will open for you!
And if you want to, well, we are in the business position to help you with that 😉 Never hesitate to let us know where we can help guide you on your exciting Tableau road! Stay tuned for our next post on the Tableau Catalog!