We primarily use the solution in order to get to know the data. Companies get to really explore and feel like the creators of their own destiny. Tableau is very different from and the other BI technologies I have used. They say that the main goal is not a dashboard; you're altering your exploration of the data.
Tableau in French is translated roughly to a blank page. You can do whatever you want on it. In that sense, Tableau is so amazing. It really helps us manipulate and understand data in interesting ways.
They have advanced statistics features that you can easily apply to your data. For example, I can do very quick calculations. In other software, I would have to code a bit to really work on that logic. In Tableau, it is drag and drop. You can drag and drop to calculate the annual growth year over year. It's so simple. Boom, there you have it.
They have advanced forecasting features. You can just select your dataset and select which model that you want to apply. You can use a stack, linear, exponential, or logarithmic algorithm. Tableau actually lets you drag and drop in order to see what a build is going to be like. Forecasting is rather new. It was introduced last year.
The maps and colors and interface are all fantastic.
The attention we receive from the partner manager would be an issue for us. The use case to have them is a bit niche. Not everyone wants a cookie-cutter analysis and it ends up being plain and not very specific. It's nice sometimes to do that. The expert analysts work on the solution once or twice or three times, and they get to a final dashboard. However, if you use a Tableau final dashboard, you can feel that it was not designed to just be used as a dashboard. Playing with that dashboard is not the end-game. It is not the final objective.
There are two types of users. There are those that are smart and proactive and constantly discovering new cases. Those are the ones that will benefit from Tableau. The others tend to just want to use dashboards, and they won't get as much out of the experience.
The data entered into Tableau must be clean. Otherwise, it won't work properly.
The support for vendors could be a bit better. There isn't much helpful communication happening.
My company has been working with the solution for about five years. In terms of myself, I have only worked with it for two and a half years.
We do have salespeople from Tableau that look to us and they do give information. However, I asked a month now today if they could give us a heads-up on Tableau's new features and Tableau's new pricing scheme for the new commercial people that have been entering the company. Our partner portal is not working anymore. We haven't been given much attention from the partner manager. We're not mad, don't think about that. However, it is something we need access to.
I stated that point with them. The salesperson from Tableau was sending emails to the partner manager to set up a one-hour chat with them to go over new features and in regards to the onboarding to new people. She hasn't answered. It's very volatile on their end, as they do change their personnel very often, and it's very difficult to keep track of that. They do not say, "Hey, Adrian, I am leaving the company. This person is the one that's going to be taking care of you guys. Let me schedule a meeting." That has been an issue.
We are using the latest version of the solution at this time.
We're partners and we're currently working with Tableau.
Those considering the solution must be aware that Tableau is not an end-to-end platform. Tableau is a data analytics platform that works perfectly well, however, it has to be given an input that is clean, that is perfect. The information has to be very structured, very clean, very perfect. Once you have that, Tableau works very, very well. However, if you think that Tableau is going to solve your data problems as a whole, you are confused because you need a middle manager to help you with that.
Some people have used the Azure components to do the data clean, and preparation and finally put it into a data warehouse or a database in an imperfect fashion. After that process is done, then you can connect Tableau. Not before. That will be a mistake. A lot of companies have suffered that due to the fact that they weren't aware they needed clean data.
I'd rate the solution at a nine out of ten due to the weakness on the data preparation side. It is not a weakness as they do not brand themselves to be clear the data needs to be clean, however, so no one should be shocked. I love it for the most part and find it a very interesting solution.
