Tableau Reviews

There are so many smart features baked into this product, it's hard to even rank them. I think what makes Tableau stand out over other software I've used is that it doesn't start with a visualization, then pump numbers into it: It starts with numbers, and then represents them as shapes on a canvas. The result is more akin to an artist painting on a canvas using numbers as the brushes and colors. As a result, it is the flexibility of the mark types, and how they interact with data types, that make this product stand out. Someone who wants to create a visualization need only imagine the intended output, then use the numbers to create the marks in that output.

A non-trivial example is that a number can be considered continuous or discrete, depending on the context. In some cases, you need to use the same number both ways in the same visualization (histogram, anyone?). The flexibility to specify how a number is interpreted in terms of how an axis/mark will be generated is visualization at a more fundamental level. It is a completely different experience than pointing Excel at a highly manipulated table to generate an inflexibly structured chart type.

The use case has been different from one organization to another. In most cases, the initial buy-in and value-add is at the analyst level. The freedom to calculate, then derive, then iterate - that never-ending cycle every analyst out there knows well - to do that, do it quickly, and in a way that is remarkably beautiful, is every analyst's wet dream. Even if an analyst never shares visualizations they create during the course of a project, the tool makes them better and faster at deriving insights of their own by virtue of everything data visualization is meant to do for humans - improve understanding.

For organizations that have the capital to take it further, beginning to push out the interactivity, reports, and resulting insights up the ladders, or out the branches of the organization, with buy-in to the more-expensive server options - well, those organizations wield a much greater force. The ability for decision makers whose decisions affect many lives, higher in an organization, or the net effect of decision makers who make thousands of small decisions every day - Tableau, used well, makes it easier to make higher quality decisions faster. The same can be said of any technology used well, to be fair, but Tableau’s beauty and speed to insight is unmatched.

In my case, I have also used Tableau as a report prototyping platform. Designing and implementing is so fast in Tableau, when working with business stakeholders who may not know the specifics of what they want, and will ultimately be using whatever reporting platform their corporate standard is on - Tableau is great for iterating through version after version, change after change, until a report is built that is exactly what the business needs. Then, specific requirements can be written for a report builder using that corporate technology - which is invariably slower to iterate on. By moving the prototyping and proof of concept to Tableau, the development hours and agile lifecycle can be decimated.

Connectivity seems to be a sticky point, but it's also a hard nut to crack at the level that I would love to see. Tableau is fast, razor sharp on the whole - WHEN you use an extract. The problem is querying the data to fill the extract is only as fast as the source system. The result is that when you start working with large volumes of data, you often must start finding creative ways to improve the performance of your query. Here's where it gets tricky. I almost exclusively use SQL Server as a source. When I want to create custom data for an analysis (or some ongoing report with complexity), I have the latitude to write custom SQL. The problem is that in order for Tableau to retrieve metadata, the query sent to the server arrives as a subquery like:

SELECT * from ([your custom SQL here]) x

Because of this, I can't use a host of very useful T-SQL techniques that improve query performance or clarity. No CTEs, no temp tables, etc. In some organizations, the argument is that if you want that kind of complexity, wrap it up in a stored procedure and call the procedure (which, yes, you can call sprocs in Tableau), but that comes with its own disadvantages, which I won't get into too much here. But that is not to mention not all report writers or analysts have the privileges to create or alter sprocs on a server within their organization.

In any case, depending on how much control you have over your database as a Tableau user, as well as the nature of the data you are pulling, you may find yourself having to be very creative just to get data TO tableau to create larger extracts.

I started using Tableau in version 7, around 2012.

Desktop deployment is a cinch. Server, I had no involvement with setting up.

The user community is extremely vibrant and engaged, especially for how (relatively) young the product is, so I have only had two occasions to call support. In both cases, they were resoundingly helpful and responsive.

Back in 2012, we evaluated it against QlikView and MicroStrategy. MicroStrategy was more complex than our organization needed, and Tableau won out on ease of use and feature set, but I don't really remember the grittier details.

Initial setup was simple and fast for both Desktop and Server, but, as I mentioned, I was not involved in Server setup.

In 2012, we used an in-house team. I was not deeply involved at the time, so I don't have much implementation advice. For a larger organization, Tableau has created a consulting arm specifically for implementation, and having read a few of the white papers put out by them, I would highly recommend using them for a large implementation.

ROI can only be attained by use, so the ROI will be a function of adoption, not features of the product. Make sure you have the culture and an execution strategy to get people engaged and using it. Compared to other BI software, it's very easy to use, but not everyone will start using it just because there is a new icon on their desktop. Figure out adoption. Focus on it.

If people are using it, the ROI will be there, but if you spend 6-7 figures on an enterprise feature set and nobody uses it, it will have been wasted.

For the prototyping situation described earlier - one complex dashboard built from scratch then implemented in SSRS - the saved development time alone paid for the Desktop license.

This is a visualization software. Make sure you are looking at total cost of ownership in the context of other BI infrastructure that is still needed to get good ROI. Management of data at an enterprise level is more than just visualization, and if all of those things are in place, this product shines. If you have dirty data, slow resources, governance problems, etc., this software is not designed to solve those problems, and those problems will stunt the usefulness you get out of Tableau.

Ease of use, speed to develop and deploy solutions. The ability to quickly develop solutions is invaluable. We are managing an immense amount of data and can more quickly correlate multiple data sources to aid in our decision making. We don’t need a large team of technical staff to develop tactical solutions to support executive decisions makers, while also developing robust work queues to aid staff in prioritizing their work or improving health and outcomes of our patients.

We are much more nimble in our ability to provide tactical data and deploy scalable enterprise dashboards/visualizations to staff within the organization. It has allowed non-technical staff to build solutions to aid us in our decision making or improving clinical care for patients across the enterprise.

- More advanced capabilities to format dashboards
- More advanced data merging from multiple data sources
- More advanced management of data extracts

I have been using it for 5+ years.

I did not encounter any deployment, stability or scalability issues.

I rate the level of technical support at medium. Staff are responsive when there’s a major technical issue, but getting answers to trivial questions are handled via forums and can take time or might not match your environment or configuration.

Qlik and Business Objects were used previously. Tableau was selected based on feedback from staff and other peers that are using the product, as well as all of the success we have experienced within our organization. The benefits and speed to develop were key decision factors. Licensure costs was also a key factor in selecting Tableau.

Initial server setup is very easy and does not take a significant amount of technical expertise.

An in-house team implemented it so we could gain expertise in configuration and how to perform upgrades.

ROI is not easy to quantify at this point, but we have gained efficiency through some initial self-serve data and faster time to discover.

Licensing can be expensive, so it’s best to determine scope and implementation plan.

Utilize the trial version and test out functionality of the product. It’s very easy to get started and as you gain proficiency, you will want to learn more and develop more advanced solutions.

Geo Spatial maps and Time Series animation with Storyboarding. The easy to use interface has really accelerated adoption. 

It lets power users like engineers create visuals on their data without waiting on a longer IT project timeline. The downside is you really need some SQL skills to take full advantage of it.

For Tableau, R is just a script interface. It is missing the R-style Plot area the data scientists want to use. They really want to overlay pieces on the plot and derive new graphs.

They need to provide a Folder hierarchy for organizing content and setting security. Creating 900 sites takes way too much work and limiting. As a result, we have hundreds of Worksheets in one long list—not good.

We had no issues with the deployment.

Performance has issues when you get too many users. The latest upgrade made it worse and had to be backed off.

The above issues brings into question how scalable it really is.

I am most familiar with SAP Business Objects Web Intelligence, but have been to classes on Tableau, Power BI, and Qlikview as part of our internal efforts to help the business choose which is right for their needs.

R and SAS are under our heading of Advanced Analytic tools in the BI space and will be evaluated in phase 2.

Plan how you need to organize and secure content up front. It’s too much work later when it becomes popular. Be sure to plan and budget for more client license bundle purchases as user growth approaches critical mass. Otherwise, you’ll be putting them on a wait list and waiting for management to approve more spending. Managing a lack of licenses is not fun.

Overall, I am satisfied with Tableau.

When compared with Power BI, Tableau is much easier.

The charts need to be improved. The drawings and the visualization need to be more accurate.

I would like to see the visualization improved.

I have been working with Tableau for four months.

I am working with the most recent version.

So far, Tableau has been stable.

I can't say that it is scalable, as I am still learning.

Because I'm taking a data analytics course. I should begin with a product. At the moment, I am our company's only user.

I have not reached out to technical support. I haven't required any assistance. The guide was sufficient. I typed in Google and found the answer to every question I had, whether it was in a form or a guide itself.

Previously, I worked with Power BI.

The initial setup was easy. They have a guide available.

The deployment can take anywhere from an hour and a half to half a day.

I was able to complete the deployment, download, and installation with the help of the guide.

For me, for right now, the price is reasonable. Tableau is free.

You won't have to do anything if you read through the guide.

I would rate Tableau an eight out of ten.

Tableau is used for reporting time in the dashboard and also for skills in maintenance and metrics. That's pretty much it.

The dashboards are great.

The solution offers very good reporting.

It's a stable solution. We've never had any issues with it.

We have found the scalability to be good.

There are no significant improvements needed. 

It would be nice to include more features on each dashboard. 

I've been using the solution for a couple of years. I've used it for a while at this point.

The stability and reliability are good. There are no bugs or glitches. It doesn't crash or freeze. 

The solution is scalable. It's not difficult to expand it to your needs.

We are a really big company. I'm not sure exactly how many people actually use the solution. In our department alone there are at least 50 users. That's a small team, really. I'm sure it's used extensively globally.

I have not heard of plans to increase usage in the future. 

I don't have experience with technical support. I can't speak to how helpful or responsive they are as I've never been in contact with them.

This product was already in place when I was hired. I'm not sure if something different was used previously.

The installation was handled before I came on board. I was not a part of a process. I can't speak to if it was difficult or not.

It's a hosted solution. We don't need a team of engineers on it from our end.

I can't speak to the pricing. We're a global company. Another team deals directly with contracts. 

I would rate the solution at an eight out of ten based on my experience and what I know. 

My client was initially using SAP BO as a reporting tool. This client added another entity to their organization and considered using Tableau for reporting purposes. The reason for choosing Tableau is because it is easy to use and we already had some developers with experience using Tableau. We have not done a complete migration from SAP BO to Tableau due to the volume of reporting still in SAP BO which Tableau cannot handle. 

When creating reports for entities with less data, we make use of Tableau. We have trained 10 to 15 developers for this reporting. It took two to three months for them to master reporting in Tableau. 

We use Tableau to create reports based on geographical maps to show the impact of natural hazards on the insurance industry. This solution offered us the flexibility and ability to visualize this type of information. We also use Tableau to host reports which are published on a weekly schedule to certain user groups. 

Tableau has data relationships that can be applied to a data source which helps build out a directory which is helpful. Data blending has also been valuable to us.

The extraction, transformation and loading of data in Tableau takes a lot of time and we do not have confidence that Tableau is showing all the data we need. This is due to limitations on data extraction which needs to be improved.

We experience user restrictions using Tableau and require a more dynamic setup for extraction of data, configuration of reports and providing access to users. 

Tableau useful for dashboard reporting, however, there are limitation on the number of rows of data you can view in a report. It is for this reason that we use Tableau alongside other reporting solutions. Tableau does not support any HTML coding in the same way Power BI does. 

There is a maximum number of tables we can use in Tableau. This could be improved in a future release.

I'm have been working with Tableau for seven years.

Tableau is a stable solution. 

This is a scalable solution. 

We continue to use SAP BusinessObjects Business Intelligence Platform. 

Tableau is a business intelligence tool. It allows you to extract specific insights and analyze data. It comes with many add ons and features including stories and dashboards. Our biggest challenge when using Tableau is the ETL size. It is for this reason we are switching to Power BI. 

I would rate it an eight out of ten. 

Right now I use Tableau for learning purposes, such as open data sources, trying to learn the various visualizations that can be done on it.

I liked the representation of the geospatial map. It was really cool to have that visual and be able to create hierarchies using the geolocation cities, states, just wording those names into appropriate provisions on the map. So that's really something nice. I feel the visualizations come out very pretty.

The price is definitely a point that can be improved because smaller firms, like my bank firm, don't use Tableau because it's an expensive tool. If there were an option that catered toward smaller firms, that would be great because Tableau does in fact help with a lot of different kinds of data sources. For instance, it lets you upload CSV on Excel. However, other tools that we currently use, such as Looker, do not let you upload Excel files for ad hoc analysis. So, definitely, this is something price-wise that can be catered toward smaller firms.

Creating variables, creating new fields in Tableau during analysis, actually adds columns to the data. That's something that could potentially give us an option. Do you want it as a column added to the data set or do you want it ad hoc in the visualization sheet? So if you create a measurement or a dimension, that creates a new column, but if you try to create a new filter directly on the visualization, it doesn't let you rename it. Basically what you see is just the calculation that you put in there. If you wanted to create something without making it an extra column in the data set, you can't just rename it to a more user-friendly short name. An improvement would be adding the ability to rename ad hoc creations if you do create a mark or a filter on the visualization. That doesn't really get added to the actual data fields.

I've been using Tableau for a few months now as a learning, research activity rather than a day-to-day activity at work. So I primarily was going to a Tableau Public Learning.

As of now, I haven't had any issues with the stability of the solution. Not any glitches.

Given that it's Tableau Public, I don't feel I could give the right answer to that. However, given that you could share your visualizations on a server without sending a file to people, scalability seems like a good option here.

I have not used their tech support, but I did refer to a textbook to learn how to use Tableau.

Tableau has resources for learning using videos as well.

My company currently uses Looker, not Tableau. I've been working on Tableau on my own time outside of work, trying to learn their free application, Tableau Public.

The setup was pretty straightforward. It doesn't take much to get it all set up.

Tableau is an expensive tool for smaller firms.

Do take time to learn the solution, because Tableau has a lot of features, a lot of complex visualization features that can make the visualization pretty powerful. I would advise people to learn it completely so they can use Tableau to its full extent rather than just ad hoc simple visualizations.

I would rate Tableau right at 8.5, leaning toward 9.