Tableau Reviews

I've used Tableau primarily to visualize data on asset performance. These visualizations pertain to reliability engineering and I've created charts and dashboards showing key performance indicators such as mean time between failure for different asset components, trend/pattern of asset behavior (different types of events occurred in the asset) prior to failure and asset grouping based on their health and performance.

Tableau is so flexible as to enable the user to show events that have occurred over the entire lifespan of each asset. Normally, this requires a bit of data-wrangling but in my experience this graphic has found a lot of favor with multiple clients.

All of these visualizations were created in a local environment (at the desktop-level) using data from .xlsx and .csv files.

In our line of work, we primarily use Tableau Desktop/Server to visualize data based on our clients’ requirements. Once, while dealing with a procurement scenario, we found that the client could save $2.00 on each unit of Part A if they ordered it from Supplier X rather than from Supplier Y.

In another case, we designed dashboards that showed data from different sensors located throughout a building. This kind of an application could enable stakeholders to monitor building climatic conditions in real time and adjust thermostats according to CO2 levels and occupancy, thereby driving efficient consumption of power.

In this way, Tableau visualizations can be used to take more intelligent decisions as they bring out patterns buried under a mountain of data.

I believe the most valuable feature of Tableau is the flexibility it offers with regard to the types of visualizations the user can create. A lot of other products in this space offer limited chart types and work in a way that provide little room for customization, if any. But Tableau allows the user to work with its predefined templates such that the end result can be a visualization that is highly customized - in terms of the design, colors, sizes, shapes and the overall visual appeal. This is an invaluable feature as it enables one to communicate more powerfully from the data.

I would also consider the ‘Create Calculated Field’ feature as very valuable. It’s one that I’ve used quite extensively. Most of the time, the data we work with will not have all the necessary features that enable us to tell a good, convincing story out of it. Therefore, it becomes imperative that we create them and extract the maximum amount of information possible from the data.

Formatting charts - colors, lines etc. - is also simple and there are a lot of options for customization.

I would like to see the inclusion of a template to create a speedometer chart. I can understand that Tableau doesn’t have it as one of its default chart types because it’s not a good way to represent the data. Indeed that’s true, but speedometers are quite popular and once we had a client who was insistent on having highly-customizable speedometers and I had to spend a good amount of time to create them via multiple workarounds. In my experience, I've seen many customers who do not want to consider alternatives to speedometers.

I’ll address these two points:

• Speedometers/dial charts are a not-so-good way to represent data
• I had to resort to multiple workarounds to create a speedometer in Tableau

First, I’ll give you a few reasons as to why speedometers are not considered to be a good way to visualize data:

1. Low data-ink ratio: ‘Data’ here refers to the data that you want to show on your chart/graph and ‘ink’ refers to the aesthetic elements of the chart such as lines, colors, indicators or any other designs. A low data-ink ratio implies that the quantity of ‘ink’ on the chart is very high relative to the small quantity of ‘data’ that is present on the chart. What does a speedometer or a dial chart do? It shows you the current state (value) of any system. Therefore, the data shown by the chart is just one number. Let’s come to the ‘ink’ part. Needless to say, there is a lot of ‘ink’ on a speedometer chart – so many numbers all around the dial, the dial itself, a needle that points to the actual number etc. The fundamental principle of data visualization is to communicate information in the simplest way possible, without complicating things. Therefore, best practices in data visualization are aimed at reducing visual clutter because this will ensure that the viewer gets the message – the right message – quickly, without being distracted or confused by unnecessary elements.
2. Make perception difficult: The human brain compares lines better than it does angles – information in a linear structure is perceived more easily and quickly than that in a radial one.Let's say I’m showing multiple gauges on the same screen. What's the purpose of visualizing data? It's to enable the user to derive insights - insights upon which decisions can be taken. The more accurate the insights, the better the decisions. So, its best that the visualization does everything that helps the user understand it in the easiest possible way. Hence, the recommended alternative to a dial chart is a bullet chart
3. Occupy more space: Assume that there are 4 key process indicators (KPIs) that I need to show on screen and the user needs to know whether each KPI is above or below a pre-specified target. If I were to use dial charts I’ll be creating 4 dials – one for each KPI. On the other hand, if I were to use bullets, I’ll be creating just one chart where the 4 KPIs will be listed one below the other and each one in addition to showing its actual and target values, will also show by how much the actual exceeds/falls short of the target in a linear fashion. As real estate on user interfaces is at a premium, believe me, this is definitely better.

Now, let me come to my situation where my client would not accept anything but a speedometer. As I’ve mentioned in the review, Tableau doesn’t provide a speedometer template by default. So when I was going through forums on the Internet I saw that people usually used an image of a speedometer and put their data on top of that image and thereby creating speedometers in Tableau.

This would not have worked in my case because my client wanted to show different bands (red, yellow and green) and the number of bands and bandwidths varied within and between dials. For example, one dial would have 2 red bands (one between 0 and 10 and the other between 90 and 100), 1 yellow band and 1 green band while another would have just one yellow band between 40 and 50 and no red or green bands. Also, these bands and bandwidths would be changed every month and the client needed to be able to do this on their own. Therefore, using a static background image of a dial was out of the question.

So, here’s what I did: I created an Excel spreadsheet (let’s call it data 1; used as one of the 2 data sources for the dial) in which the user would be able to define the bands and bandwidths. The spreadsheet had a list of numbers from one to hundred and against each number, the user could specify the band (red/green/yellow) in which it falls. The other data source (data 2) was an Excel sheet containing the numbers to be indicated on the dials. Then, in Tableau, I created a chart which had 2 pies – one on top of the other. Both the pies had numbers from 1 to 100 along the border, providing the skeleton for the dial. The top pie used data 1 and had the red, yellow and green bands spanning the numbers from 1 to 100. I then created a calculated field having an ‘if’ condition: if the number in data 2 matched the number in data 1, the field would have a value ‘yes’. Otherwise, it would have a value ‘no’. This will produce only 1 ‘yes’ and 99 ‘no’s’ because there will be only 1 true match. I put this calculated field onto the ‘Color’ shelf and chose black for ‘yes’ and white for ‘no’ – this formed the content of the bottom pie. So the bottom pie had 99 white colored slices (which looked like one huge slice) and just 1 black slice (which looked like a needle). I made the top pie containing the red, yellow & green bands more transparent and this gave the appearance of a needle pointing to the KPI value, also indicating into which band the number fell, thereby enabling the client to gauge their performance.

One to three years.

I've not directly contacted the tech support team of Tableau Software myself but whenever any clarification was required regarding the creation of a particular visualization, I've found many discussion forums and blogs, the contents of which have been extremely helpful.

I have also worked with Microsoft's Power BI and I've found Tableau to be far more flexible and user-friendly in terms of the variety of visualizations it allows you to create.

Our primary use case of Tableau is for reporting purposes for our clients. We provide analytics for clients, giving them the ability to build reports. We also have our own product which provides the data analytics platform. I'm a product manager and we are a customer of Tableau. 

I like the data flow and the ability to easily manage the data. The solution also has good building capabilities. When we apply filters, we tend to order different reports and it becomes easier for us.

The solution requires a lot of user training before reports can be created. That can make things difficult and require us to have Tableau specialists. It's difficult for a newbie to start developing reports. 

Tableau queries and analytics, as well as development could be improved. The solution could also include an option to incorporate more open source libraries. I know Tableau has this closed loop so they might not want to provide that but if they did have integration capabilities with open-source libraries, I think that would be great. 

I've been using this solution for three and a half years. 

This is a stable solution. 

This is a scalable solution. 

We don't generally need technical support although the clients do but I'm not sure if they provide good service. There are Tableau videos we can use if necessary. Whenever we need some solution we go to Tableau training and go through the videos.

People who have always used Tableau want to stick with it but those just getting into the field will look at options that can provide almost a similar functionality with the main difference being the cost. It's a trade-off between the different features offered on the solutions in this market and the cost. 

The initial setup is straightforward and can probably be completed in two or three hours. The client is responsible for maintaining their own solution, we only implement. If they want to upgrade the platform, that's their responsibility. 

Licensing is charged per user, I believe. Even if they're just providing you a minimum specification there will be added costs if you need more processing power. If you want to connect to the data sources, then that needs to be included in the complete solution. It's an adaptive cost. 

I would recommend anyone looking at this solution to check the validity of the business case. If you don't have a very expensive business case and you're going to be on the data processing side, I wouldn't necessarily recommend the product. But if you have standard templates and can just put in the data, export the defaults and send it, then it's a good solution because there's no complexity.

I would rate this solution a seven out of 10. 

We use this solution for enterprise reporting, dashboarding, and insight.

We have an eight-core server. There are up to seven hundred unique consumers weekly, and twelve hundred monthly. There are twenty-five power users that publish to the server on a regular basis.

This solution has transformed us from an Excel reporting environment to one of visual exploration. We don't just look at the numbers, we can easily explore why a number is what it is.

The most valuable feature is the "drag and drop" environment. We also appreciate the ease of use for adoption with "row-level" internal customers.

I would like Tableau to handle geospatial data better in terms of multiple layers and shapefiles.

Whereas we used to present statistics in a traditional way, we now have interactive web-based presentations. 

The most valuable features are data discovery and fine visualizations.

The SQL programming functionality needs to be improved.

It is a very stable solution.

Ths scalability of this solution is good. It depends on your DW design, as opposed to limitations in Tableau. If your DW model is poor then Tableau is not miraculous.

Tableau does not have good technical support.

We previously worked with Qlik, but we switched to Tableau because of its visualization and simpler way of programming. Tableau is also good for data discovery.

The setup and support are not very expensive. In that way, it is not a complex technology.

We are a software consulting company and we have implemented tableau for more than ten clients. 

We are a consulting company and do not track the ROI information for our customers.

Be careful with the Tableau Viewer's licenses, and stay with the right number of users.

Before choosing this solution we evaluated Qlik, BusinessObjects, and Oracle BI.

Be careful with tableau support. Stay in touch with the professional partners because Tableau itself does not have the right number of developers or people for support.

This product is for non-technical users who know, or may not know, what they need but would like to automate their processes.

It has been the best tool to work with from a self-service point of view. The explorer capability in Tableau allows analysts to connect to data sources published on the tableau server, build their own product and customize reports.

The extremely intuitive and user-friendly UI helps naive users easily click and connect, drag and drop, and build fantastic visualizations. Of course, the back-end data structure needs to be strong for them to be able to do that, but it saves them a lot of time.

Licensing and pricing options could be made better so that more users would be able to use it. The biggest concern any organization has is its budget when trying to implement a new product. Tableau is an extremely powerful tool and hence expensive, but if there was a way to cut down the cost they would end up attracting more users.

We use Tableau and Tableau Server for data visualization. We have a Global Tableau Server used by five thousand users on a monthly basis, with fifty thousand email notifications and more than five hundred workbooks for sales, marketing, revenue management, and operations analytics.

The solution has improved the organization by allowing quick access to data visualization and data exploration. Also, it helped to have a global server used as a repository to see all of the reports in the same place.

The features that stand out in this solution are:

• Scheduled extract and the multiple connectors are fantastic.
• Tableau Prep is fantastic.
• Tableau mobile on the tablet is also great for operations and the field users.
• "Ask Data" is good.

The performance could be better. At times, it can take up to one minute or more to open a workbook, which is very frustrating for the users.

Stability is okay, although performance is slow on our side.

Our solution handles five thousand users per month.

Premium customer service and technical support are fantastic. Best in class!

We previously used Cognos and Power BI. We switched because with Tableau, you do not need IT support. Users can create their dashboard really quickly.

The initial setup was a bit complex, more so than expected. I would use a fully managed solution if I had the choice again.

Our in-house IT department implemented this solution.

The initial cost that is set according to CPU cores is expensive. You need to go with at least thirty-two CPU cores for five thousand or more users.

Before choosing this solution we evaluated Qlik, Domo, and Power BI.

The solution is very good. Loved it and the employees also love how quickly they can create a workbook and share it. Overall, a great solution and a great team.

We use this business intelligence tool to build dashboards to display some of the statistical and analytical information that our company gathers. We develop a precision medicine software platform that enables academic and community healthcare providers to implement and scale precision medicine programming. We capture clinical data, genomic and other molecular data, biomedical knowledge, and the relationships among them. We also provide integrated complex genomic and clinical data to clinicians with actionable insights. 

Previously, we built the dashboards manually but this practice proved to be inefficient and ineffective since it meant we spent a lot of time debugging. It's was hard to find developers capable of doing that kind of work at scale. Since the Tableau community user base is so big and a lot of people can use it; the widespread support is one of the biggest benefits. Besides that, it's a fantastic framework to build dashboards and innovative visualizations.

One of the most valuable features is that the solution allows users to build interactive dashboards. This allows the end user to modify the criteria or the filtering if need be.

As far as for my personal use as a QA Engineer, I really value how extensive their API document support has been.

Improvements can be made in template support. The workbook file structure is really hard to version control. If there was some sort of version control support offered particularly for workbooks, that would help big time.

Another note is that the interactions within the UI are not fast enough and in certain instances, there have been issues with the intuitiveness of the tool. Such as delays in configuring and achieving some specific effects. 

I have to say Tableau does have excellent and extensive online support.

The solution is stable. I've never had any problems.

My impressions of the scalability of this solution are that there are ways to make it as scalable as you want. There have been some issues with the amount of the data that we had to use on the platform. We ended up using the extracts. It works fine now. I would say it is scalable.

I haven't contacted their live support or emailed them. Their documentation is fairly extensive and we also had a training session conducted by one of their partner companies. It was the Tableau Accelerated Course and that helped a lot.

The initial setup was straightforward with respect to the deployment. 

Tableau provides a UI which can be used to build a clear graphical visualization that allows quick and easy data comprehension. This functionality really helps turn data into scalable insights. This makes things a lot easier for people who don't have coding experience and with dedicated people focused on managing the visualizations, not requiring them all to be developers or to have any coding experience is a real plus.

If I was to give this solution a rating from one-to-ten, ten is the best, I'd rate it a 9 because it does all that we require of it and more. I would recommend this solution to my colleagues from another company. It's a nice tool to work with.  

I have a lot of experience using Tableau for the Healthcare Market. I use Tableau for visualization and reporting mostly. Main observations:

• Tableau is nice and smooth. 
• Tableau is quite user-friendly and easy to use. 
• The digital agents were really great. 
• Clients and customers liked the visualizations. 

Overall, I got positive feedback from clients by using Tableau.

I work for clients. That is my business model. Business people really like to see Tableau. They love Tableau because it is very user-friendly. The platform provides an easy to use interface, which is what most people like about it. 

Being easy to use is more important to me than the look and feel Tableau gives to your data. Nevertheless, data analytics is what we value the most. 

Tableau definitely has a big user community. If you get stuck or anything, you can easily seek help through that. Whenever you do this, you get good results.

The diagram drop facilities help to double up hard drive reports. The map facilities and the ability to connect with different data sources are the most valuable features. 

Tableau has a lot of different connectors, many of which are very new. You can connect many different data sources with Tableau. 

Overall, it was a good experience with Tableau and the visualization looks quite attractive with the proper combination of colors.

I have a lot of experience on the desktop version of Tableau. My recommendations for improvement for Tableau would be:

1. From the developer perspective, the data connection handling the target data set is what most needs to be improved. 
2. Tableau keeps evolving with each version. With Tableau 192019.2, they're coming again with some more features. 
3. Data preparation is where Tableau needs to work a lot on. Every time with Tableau you have to invest a lot of time preparing the data before you start using the visualizations.
4. Tableau doesn't perform well on big data processes. Suppose I was working with a file of like 1 or 2 gigabytes, then in that case Tableau is really slow. 

Sometimes I feel that Tableau is too slow when you have a big data file.

It's quite stable, aside from the data file which is not. Otherwise, Tableau doesn't hang.

Good scalability. Not that bad, not that great, it's good.

I didn't need technical support with Tableau.

We don't have any preference for other solutions. We depend on Tableau for the solutions based on the client's requirement. If a client requires Tableau, we develop the application and customize it.

A lot of complexity happens initially. Tableau is a little bit too complex. I started using the clear tool and application. Then you will feel comfortable with the tool and with the data. 

There will definitely be some tough, complex things in your development, especially with the data. The data preparation (combining everything else) has to work. 

Initially, all the data preparation tools have that kind of experience. In the beginning, you have some tough times and little complexity. Once you resolve this, the future and further development will come relatively easy.

First, clients should be comfortable with the existing resources or existing platform which the organization is using - that is one of the very important aspects before you decide on any new tool or any kind of new technology. 

Second, you want to go ahead and invite a new application into your current system. Ask how compatible the application is before you decide on any new product in your organization.

Third, you should consider if your employees are comfortable with the new incoming technology in terms of whether it’s easy to learn or adapt. Ask how comfortable your employees are before you bring any new tool into your organization

These are the key important points. I will rate Tableau at eight out of ten because there will be some shortcomings in the application that are not up to the mark.