There are a plethora of data tools out there for professionals to use. All with their specific use case and strategies. Tableau is one of several highly utilized data visualization tools. It is easy to use, can be connected with multiple data sources, including flat files, databases, CRMs, etc. Honestly, for a non-technical person, it is probably one of the best tools.
However, for all the good Tableau has, it has a dark, hidden secret….
What you may ask? It is quite simple. It is too easy to use!
Wait, What? How does that even make sense. Aren’t tools supposed to be easy. Shouldn’t we just be able to click twice and have a beautiful report? Yes, you should be able to do that, we are in total support of simplifying technology.
However, there is the risk of failing to plan in these situations though…
Now, if your team is accustomed to proper software development procedures, and has good SDLC practices, you are in good hands. If, however, your team is a bunch of bright, and intelligent business analyst who are eager to impress you. You might have problems.
There is a fine line between the constant prototyping and documenting every literal change request(including font changes). Somewhere in the middle, is where you need your BI and Data Science teams to be. They need to build you reports quickly but they also need to ensure they build them in a maintainable way with proper QA steps, analyses stages and risk assessments.
Where does the ease of Tableau fall into all this. If you can make a report in a few clicks, the temptation to not actually think about what you are creating, what data sources it relies on, and how to QA it. How do you know the report will always work and that it is always accurate? Do you know if your data is good? Who manages that data? What happens if the data source disconnects or changes? Did you contact the owner to make sure they know you are using their data? And most importantly, did you check if you already have this report and do you need to revamp it, or not make a new one.
We brought up just a few questions that need to come up when planning any data driven project. We were mostly using them as examples to why Tableau can cause inexperienced teams problems.
Tableau is a great tool. In fact, I love it for prototyping, and mock-ups. We can demo an example report for a client, or executive in a range of 30 minutes to a few hours. The report might even be usable at that stage (This depends on how well I know the data source). That doesn’t mean it should be. Tableau is created to be robust, but it has a lot of issues that need to be considered.
Besides being too easy to use (Yes, we know that sounds weird). Tableau isn’t always as smooth with integrating with technologies as you may think. For instance, we once created a pretty cool report that you could track all your invoices and click a link to them using tableau. Pretty snazzy right! All the executives were raving how they could actually track their invoices. Before..they were literally just told they owed money..
The invoices were connected to an internal app that only worked on IE. So the end-users had to use IE to get to the invoices. This was fine for about 6-7 months. Then, one day, the company updated the Tableau. Things should have been hunky dorey right?
Of course, there was one problem. This version of Tableau worked terribly in IE. It would throw errors, freeze up and just cause constant issues. We couldn’t do anything to fix it and because our internal tool only worked on IE, there was no winning. Obviously, we can’t go into the source code of either program and try to get it to work. Now, a dashboard that our entire executive team relied became unusable.
Some of this is due to the companies haphazard approach to third party applications. However, it is also a good example of how sometimes, you miss mapping out risks, which makes it even more important that you analyze the each component of your future solution.
Tableau is really a great tool, but like any tool, it requires a decent understanding on how to implement it. Tableau can be very dangerous. As the great saying goes, with great power, comes great responsibility(To learn tableau best practices).
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