Tableau Reviews

• Prototyping
• Visual representation
• Quick for report readers versus tables and numbers in most other similar tools

As a consultant, the organizations I've been at like the ability to see a visual report. This is can be done fairly quick as opposed to numbers.

• Difficulty when moving 'outside of the norm' where 'workarounds' are needed
• Difficult if you want to present reports as numbers and tables
• Free version only available for educational users but not for consultants working in many organizations (and could therefore be introduced to it).

2-3 years.

No issues encountered.

No issues encountered.

No issues encountered.

Customer Service:

Good as there are various methods of finding answers and fixes.

Technical Support:

Good again as they have various methods to ascertain answers.

I have used many other solutions as a BI consultant including Discoverer, Brio Query, Impromptu, Bus Objects, etc. Tableau seems to be popular right now as, again, the presentation and data model are quite different than the others

It is a straightforward setup.

In-house and via myself.

As mentioned in previously, many clients choose Tableau due to its data model and presentation layer.

As a consultant, ALL BI tools use phrases like 'it empowers the end user', 'end users can create reports in minutes', etc. However, in the real world, end users can create SOME reports once middle layers are built, training is given, limitations and security is imposed, etc. For a complete system, IT departments and consultants must install, set up, create initial works and then have SOME power end users involved. NO tool bypasses this and gives all to end users - and if it did, security would be lax.

Easy setup and intuitive drag and drop functionality. Easy connection to a range of different data sources. Range of visualisation models, constantly extending with new releases. Dashboards and story-telling.

It has allowed a shift from IT-centric enterprise reporting to business-centered development of ad-hoc and enterprise reporting, in partnership with IT. This brings significant extra agility to the organisation and a model of greater co-operation between business units and IT department.

As with all products there are many areas that can be improved. Tableau actively encourages suggestions from its user community, allowing for voting on what features to include it future releases. http://community.tableausoftware.com/community/idea

3 years, starting with Tableau 6.0.

No significant deployment issues. With a sufficiently resourced infrastructure (CPU/RAM/Storage) the product is easily deployed. Tableau helps with the necessary specifications.

It is a mature and very stable product.

Scalability is very good, especially with release of Tableau 8 which brought 64-bit and multi-threading. Extends to hundreds of users on a single server in my organisation without any issues and has capability to include clusters of servers for larger organisations.

Customer Service: Very good. Very little need to deal with them on an ongoing basis due to the robustness of the product but on the occasional time we need some help they are very responsive.Technical Support: Initially very good with strong technical support easily reached. As the Tableau user-base has grown quickly there are more formalities to reaching support now but still top-quartile. Again little need to lean on them due to the stability of the product and strong online documentation and forum support.

Oracle Discoverer. Switched because we needed to move to a partnership model between IT and Business units. While Discoverer allowed for power users in the business to author reports its metadata layer and underlying database technology required more intensive IT support. Tableau enables the business user while giving more agility to work together to deliver ranges of enterprise solutions.

Straightforward. Get a good server and provision it according to Tableau’s technical advice, install, and you’re away.

Mainly in-house, some support from Tableau themselves and also a local Tableau partner. Expertise of partners not great at the time in Europe but has matured considerably over the last few years.

Commercially sensitive.

Commercially sensitive.

Sas Microsoft SSRS Qliktech Oracle OBIEE Microstrategy

Assess your own strengths and create a preferred architecture. Then see if Tableau fits some of your needs. For anything significant in scale you will need a robust underlying data architecture, it won’t do all of your ETL. While it is possible to create and deploy artifacts very quickly without formal training, it is worth sourcing some to help you leverage the best features of the product.

It was for dashboards. The key use case was for creating visibility to performance metrics for the leadership team. It was the most recent version, and it was deployed on-prem. 

The key use case that we were going after very specifically created visibility to performance metrics for the leadership team. So, it allowed us to give that common view of performance metrics and drive business conversations based on the common shared set of facts. We were able to expose data and relationships that we otherwise couldn't do in our enterprise system silos. From that perspective, we were incredibly successful in really driving performance. When you combine that with some real championing in the business and with some leadership to push it down, the fact that it was Tableau wasn't as relevant as the fact that we had the championing pushing the process and pushing it down.

The number one thing was just the ease of getting something up quickly. The other thing that was good about it was that it was fairly fast for decent-sized data sets in terms of performance and run time.

From a downside perspective, some of the more advanced modeling techniques are actually fairly difficult to do. In addition, I just fundamentally disagree with the way you have to implement them because you can get incorrect answers in some cases.

One of the key challenges is that you never know whether it is how your developers developed it or whether it was the tool. We did find that once we got into more complex models, the ability to keep objects that should tally the same way but didn't became more and more difficult. That was probably the big thing for me. I don't know enough about how the tool was developed to know whether that was because they didn't follow a recommended practice. That was probably the number one thing that I found frustrating with it.

When we started to try and get into some very granular data sets that had some complex relationships in them, the performance on it degraded pretty quickly. It did degrade to such an extent that we couldn't use it. We had to change what we were trying to do and manage its scope so that we could get what we wanted out of it or reduce the scope of what we needed out of it. It doesn't have a database behind it, per se. So, while doing some of the more complicated things that you might otherwise do on a database, we started hitting some pretty significant challenges.

I used it for about three years.

Tableau worked fairly well for straightforward data sets, but it struggled when we got into the more complicated data sets and larger data sets. 

We were able to deploy it fairly broadly without a whole bunch of work. From that perspective, it worked fine. I was deploying my stuff to about 200 users across Canada, and I don't think we saw a blip on the server when people logged in. It was fine. If we were to roll out some of the bigger applications broadly, like the ones that we were having performance challenges with, we probably would have crushed the box. We would have had to get more CPU. Most likely, it would have been a memory issue, but we never hit that inflection point.

There were about 200 users of the solution. It went all the way from the equivalent of a senior vice president and all the way down to the equivalent of a line manager. So, we had business unit leaders, vice presidents, and operational managers.

It was being used extensively for a specific use case. There were lots of other use cases that it could be used for, but there needs to be an appetite from leadership to go, drive, and commit resources to go do that.

I didn't have to deal with technical support. Mr. Google is pretty good on the topic.

We had previously used Cognos to do the exact same thing. The only reason why we replaced it was that the business decided to go towards Tableau. Otherwise, there really wasn't any real reason to replace it. It was probably a little bit easier and more interesting for people to learn and to develop applications in the program than in Cognos. The ramp-up time to get to reasonably proficient in Tableau plus the support through Mr. Google made it a lot easier for me to get resources and do development on Tableau as compared to Cognos.

The organization decided to move away from the old platform. So, basically, I was lost when they asked me to shift off so that they could shut it down. I personally prefer the previous platform. I understood it very well. I had used it for years, and it worked just fine. For the most part, the challenges that we had on the old platform were not resolved by Tableau, which just reinforced to me that it wasn't a tool problem. It was a people problem.

It was pretty straightforward. The big thing that confuses people in a project that involves Tableau is that Tableau is a very visible but small component of the overall solution. That's because 80% of the work is data. It is not Tableau. So, Tableau is actually a fairly small component over that overall solution. It took a few days to get it up and going. Almost 80% of the work is actually on the data side, which takes forever, but the actual Tableau component of it was pretty straightforward. It was not that difficult.

You can get a Tableau dashboard up on a weekend. It is not hard to get something up and running. It is pretty trivial. It isn't any more or less difficult than any other tool to get up and going. I've used a number of them, and they're all pretty easy to get up and going. Tableau was the first one out of the gate with this democratized data perspective, where they were going to do departmental BI and up to enterprise BI years ago. Now, they now charge a fairly hefty premium to leverage that product. It is not a cheap product.

In terms of maintenance, it can take as much or as little as you want because it just runs. So, technically, you don't have to have anybody to do very much. You just need a very skeleton crew to operate as is. The challenge that you run into with solutions like this is that you need to continue to refresh the information with new and different views because people want to know more, and they want to go deeper into it. It is not a function of the technology. It is a function of the use case. So, you tend to have lots of new requests for new reports and analysis, and that's where you tend to have more challenges.

We didn't get into analysis users who are able to sort of do a little bit more themselves. There were viewer licenses where you are just using preset reports, but there are obviously additional training and things like that, and you have to deal with it if you start getting into more advanced power users.

I was at another company, and we were the integrator.

It is fairly expensive. I have no idea what they paid. We were on an enterprise license, so whatever it is they licensed at the enterprise level is what we paid.

A good chunk of it has got nothing to do with the tool. It has everything to do with your leadership and your governance requiring it. We had our IT team roll up Tableau multiple times and not a single person used it because there just wasn't enough leadership support to use it. There is nothing wrong with the tool, and it worked fine for what it did, but every time I logged into it, I go, "Okay, but what did you want me to actually do with this? I see all this information. I understand it clearly. I'm not sure what I do with it though." So, without that additional guidance from leadership, rolling it out is irrelevant. You need to have that strategic leadership associated with it.

The key piece of advice would be that you got to look beyond your tool. You need to look at how you're going to get this information used in your organization. What kind of leadership support, governance support, and ongoing support are you going to have? It is all based on trusted data. The value of the tool is based on the quality of your data and the leadership's support to use it. So, if you don't have high-quality data and you don't have leadership support to use the data, you don't need any tool because nobody is going to use it.

I would rate Tableau a seven out of 10. It suits the purpose, but in and of itself, I don't think it is significantly better or worse than its key competitors.

On-premises

User interface is designed for ease of use for non-technical users. Users can pick up the product without attending training session. This is a plus.

I have only used it to demonstrate the ease of use to financial type users in the commercial market. It is used in academia as a simply learning aid for data visualization.

Integration with big data platform is a plus for any BI tool. They need to perform ETL/ELT operations with a direct connect to Hadoop ecosystem and RStudio for data quality tasks or offer a similar features.

Two years in academia and briefly with the State of Texas in a three month evaluation project.

No.

The free mapping component needs some enhancement for a better quality of geographic information, but it does connect with a ESRI mapping server for optimal data visualization of geographic information at an additional cost,

Never used it, but the training needs some online learning courses for Tableau administration instead of relying on partner relationships to provide this training.

I did not switch. I use QlikView, SAS Analytics, TIBCO Spotfire, and IBM Watson for college instructor roles.

I only used the desktop version for evaluation of the product, and the student version online in academia. It was simple to install, but I am not sure about the server configuration.

Pricing is fair for small business groups, but it also depends on the scalability that they need with the cartographic integration for better maps.

Great tool.

The ability to connect multiple data sources, build data extracts, and display said data in an automated, graphical, format is the key driving factor insuring I continue using Tableau. While there are plenty of other tools on the market, such as Report Builder or Crystal Reports, Tableau is the first I have used that allows for such wide spread data integration and presentation in a visibly pleasing format. Moreover, the data extract function of Tableau has hooked me into using their tool over any other. Specifically, the ease of extracting and automating report generation from these extracts.

Tableau has allowed us to build automated weekly dashboards that explain our organisation's pipeline. Moreover, these dashboards have resolved long standing time sinks which have freed up resources to focus on ever larger and more interesting BI projects. Additionally, we have used Tableau to increase the range and width of reports we are able to generate on a weekly basis.

Tableau development has an increasingly large learning curve. It is marketed as an upper management tool that anyone can dive into. However, trying to develop even simple tables within Tableau is an exercise in frustration and patience. The end results cannot be denied, but the path to getting there is not for the lighthearted.

I have used Tableau now for 2 years.

Customer Service:

Tableau customer service has been incredible. Not only do they have an active community forum, but their account managers have been very pleasant to work with.

Technical Support:

Out of five, I would rate technical support a solid 4.

I have used Report Builder and Crystal Reports. Switching wasn't really my decision, as the other tools used were at different organisations. Since then, I have tried to move back to other reporting tools, but found them lacking in functions I hadn't even realised I had come to rely on!

Setup of Tableau was the easiest of any reporting environment I have used.

We implemented Tableau through a vendor team who were helpful in getting us off the ground. That being said, any reporting tool is dependent upon the data set it connects to. As such, real value has only appeared from Tableau after long usage and learning of how to use its myriad of functions.

Stick with the development process, try a report over and over, and use Google to search out answers to those questions you think have no answer. Take it from me, if you can build it in Excel, then you can build it in Tableau. It just takes time and effort. Also, it may not look EXACTLY the same, but you can get it pretty close. In some cases even better.

Dynamic interactive visualisation and publishing to server for distribution are the most valuable features of this product.

Used on client projects, it was mainly helpful for visualizing proofs of concept for further implementations.

Data preparation and joining different data sources is still not very intuitive and could be improved.

I have used it for three years.

I had no issues with deployment, stability or scalability.

Customer service is very good, very responsive and helpful.

Initial setup was very straightforward, no issues encountered.

The pricing is complex and could be simplified.

Some very good and fancy visualisations are possible with "tricks" (not very obvious how to do it). It is very helpful to use the Tableau community to see if the visualisation one is looking for is possible and how to do it. There are also many ways to get to a result, so don't look for one perfect solution as long as you get what you want.