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.

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.

Tableau is one of the most intelligent and dynamic visualization tools I have worked with. It provides dynamic adjustments of measures and dimensions. The reason this is useful is that it gives a business user multiple dimensions of data to look through. From these you can infer interesting business operation data characteristics.

Operational improvements have resulted from the efficient creation of ad hoc data visualizations in a timely manner.

The key feature of Tableau that has room for improvement is its performance with structured and unstructured data. I'm not sure I would suggest that Tableau go for a hardware oriented solution for this. Nevertheless, that would not be a bad approach to enhance the product and align with current marketing trends and its competitors.

Three years.

There were few issues with the stability of the product when there were features such as built-in data processing using TDE (Tableau Data Engine).

Not a lot here. Pretty scalable.

I would rate it as between very good and excellent.

Yes, we used MicroStrategy in the past. One of the reasons for the switch was to have more ad hoc data visualization and a more user-friendly tool for business; one which involved less coding and more GUI work.

The initial setup was not so straightforward. We had minor issues installing it across the enterprise, due to diverse technology in different business units. But none were actual showstoppers.

The pricing and licensing are generally high with Tableau. I thoroughly encourage their recent initiative of going to a “Tableau as a Service” business model, which aligns well with enterprises and also small and medium sized organizations. It even works for individuals who would like to learn Tableau and its core strengths.

We did evaluate QlikView. We actually have both in place, for various reasons.

The key point is if you would like to have faster, ad hoc and quick data visualizations, I would strongly recommend Tableau. But for enterprise-wide deployment and migration across different environments, I would say Tableau has room to improve further.

Ease of use, polished visualizations, all data elements are treated as discrete, the story-telling feature, self-service, excellent for visually exploring data with unknown questions.

Tableau is used in our Platform-as-a-Service offering for data visualization/exploration, seeking to retire a larger BI platform using it, good customer adoption/feedback.

Metadata/reuse, performance/scalability at high data volumes + high user concurrency, disparity between desktop vs. web versions – need to address enterprise requirements in general.

I have used Tableau for two years.

No issues with deployments/stability.

It does not perform well when you cross into TBs+ of data and thousands of users.

Technical support is very good.

For our PaaS data discovery needs at the time, we reviewed MicroStrategy 9.4 Visual Insight, which was not up to the capabilities/ease of use that Tableau had at the time.

Initial setup was straightforward, it is not a complex system to install.

We implemented it in-house, limited to no need for external assistance.

The ROI is unknown.

Licensing costs continue to increase in Tableau and in QlikView, which we also use, forcing us at some point to consider consolidating to one and/or turning some existing/owned MicroStrategy licensing inward to replace, if the upward pricing trend continues.

Pick the right tool for the job/consumers of the products. There is not a single product that can cover all personas/use cases well or there would be only one product out there commanding the world – and there’s simply not just one. Tableau is great if the targeted users want highly polished visualizations of the data and from an exploration use case, the question(s) for the data are unknown.

Ease of use (including frequently used calculations), drag and drop and interactive data visualization are the most valuable features of the product to me.

• Helped organization to identify the best time to roll out the campaign for summer cruise booking.
• Measured health plan product performance to identify health plan product(s) where organization is losing or making money.
• Source-to-destination mapping for health plan members to determine how far members travel to their primary care physician’s office from their residence to identify opportunities for service quality improvements.

We need a Tableau connector to connect to other BI tools like SAP BusinessObjects.

I have been using this product for over three years.

So far, I have never encountered any issues with deployment or stability. I do feel slowness rarely when I try to get data directly by connecting to Teradata database using SQL Query.

Technical support is excellent.

I did a POC with Tableau for my current organization and compared this tool with other BI tools.

I recommended Tableau for the following reasons: truly mature product, price-performance balance, ease of use, lot of flexibilities in regrouping the data on the fly, most of the frequently used calculations are built-in and very easy to use - unlike some other BI tools, which are quite clumsy - and for best interactive data visualization capabilities. Most importantly, a non-IT person can develop a simple dashboard without any IT help.

Initial setup was very straightforward.

I installed the Tableau desktop on my computer. Tableau servers are installed by our internal admins. It’s an easy installation and doesn’t need the vendor’s help.

Sometimes admin gets overwhelmed after Tableau is rolled out in the organization as users get up to the speed in a very short period of time, because of how easy it is to use the tool. Therefore, system access and resource planning should be done and properly planned ahead of time.

People should be aware of the fact that Tableau doesn’t have a semantic layer. It takes a good amount of time to prepare the dataset / data structure. Once the dataset is ready, the data visualization part doesn’t take much time, even for a fairly complex dashboard, because the tool is very intuitive and easy to use.

The ability to analyze data patterns in more visual dimensions (size, shape, color) than are realistically possible in Excel is the functionality most valuable to me.

Calculated fields are relatively simple and may leave a user wanting. Joining between multiple datasets also needs to be improved. (I heard this is an improvement that will be made with the version 10 release this summer.) Source data formatting requirements are a little particular, and reloading for new users can get repetitive.

I am a management consultant, and I have used this solution for multiple clients over the last two years.

I never had to use customer service.

Initial setup was extremely easy; when downloading the trial version or purchasing, just accept the defaults. There aren’t many ways you can screw this up.

I’d suggest taking the following steps:

1. Define what you want to get out of the tool. (People don’t always need these types of solutions, and this becomes evident once they actually get in there with the data they have.)
2. Make sure you have the existing data needed.
3. Download a trial version and play with the software and develop prototype dashboards and analysis
4. If you actually have a recurring need, then I’d look at purchasing Tableau desktop. If the need for use and analysis extends to many across the organization, Tableau Server could be your best option.

I also evaluated Qlik and Spotfire, but found Tableau to be more intuitive and visually appealing.

This product is the best visualization solution on the market. My rating is based on ease of use, visual appeal and additional functionality over Excel.

The best features of Tableau include:

• Freedom of connection: Its ability to connect to practically any database. There is no need to go through cryptic ODBC or other driver setup procedures.
• Freedom of exploration: The ease one can explore a data table. With simple drag and drop, you can produce easily readable cross tabs and paretos on-the-fly to learn everything you need to know about an unfamiliar table.
• Freedom of expression: You can pretty much build any type of analytic structure you need to analyze your data.
• Built-in visual best practices: Interfaces are clean and simple. You have to work hard to produce an ugly chart in Tableau.

With the ease of using Tableau, I am able to set up basic analytic structures in the meta data (dims and measures) with some starter chart types, then turn over to analysts who can then ask all the detailed questions of the data on their own without having to come back to me for every minor change.

• They still need to improve advanced query functions. Level of detail and table calcs have improved but still are difficult to use, especially when working with large data sets.
• The custom query editor has lots of room for improvement. If Tableau can add features and functionality here, it would be easier to work with the database in one environment, instead of having to open another query editor to develop custom queries for advanced analytics.
• The formatting interface is the one area that has lots of room for improvement, as well as the ability to be more precise in formatting. At the moment, it is much more of an all-or-none proposition.
• More integrated statistical functions.

I have used it since 2009, Tableau 5.

I have not encountered any deployment, stability or scalability issues. Although I do run into performance issues with Tableau server from time to time, it is not always easy to identify the root cause.

I have had so little need to use customer support, I can’t really rate them. Nonetheless, the few times when I have called, the level of understanding of complex data issues at the first few levels of support seems to be on the light side.

For the desktop edition, initial setup couldn’t be simpler. For the server edition, it is a bit more involved but that is to be expected.

It was implemented in house. For the server edition, an experienced server admin would definitely make the final install better.

My clients find the price tag for the desktop edition high, so they typically try to use the server/interactor edition, which for an analyst just doesn’t provide enough functionality to get the job done. Hopefully, as Tableau builds scale, they will be able to bring the price of the desktop edition down and get on more desktops, like Excel.

I have evaluated other competitive tools but in the end, my clients have always gone with Tableau.

The Tableau on-demand learning resources are fantastic to help a new user get going. There is a robust user community that is very generous with their time and knowledge to help you get through the learning curve.