Tableau Reviews

We use this solution to process and create reports for management. 

Within our organization, 10 people in marketing use this solution.

With Tableau, we can create our own reports which in turn, saves us tons of time as we don't have to wait for IT to do it.

Tableau is easy to use and it has great predictive features. 

It would be nice if we could export more raw data. Currently, there is a limit as to how much data you can export.

I have been using Tableau for roughly three years.

Tableau is very stable.

The technical support is pretty good.

The initial setup is quite straightforward. It's not too complex.

We deployed this solution on our own.

The price of this solution could definitely be lower. It's quite expensive. We're on a monthly subscription — I am not sure exactly how much we pay.

Tableau allows us to go deep inside the data — other solutions, like Excel, don't allow you to do that.

As a BI tool, I would give Tableau a rating of eight out of ten — it's one of the easiest BI tools available; however, it's not that easy to manage orders. It's really user-friendly for individual users, but it may not be suitable for large organizations.

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.

I knew this service from my academic field and was able to transfer it to the workplace. It is an excellent tool for data capture, processing, and visualization. The application of statistical models on the data displayed is very useful, and it is not complicated.

Tasks which may have involved days, even weeks, I was able to solve them in a very short period of time, thanks to Tableau. 

Information which was housed in a database, used for exploring, ordering and applying statistical models for analysis can be complex when involving different software. However, it was easy to do using Tableau exclusively.

What hooked me to this service is the combination of very pleasant, interactive graphical visualizations along with the application of advanced statistical models (in some cases).

The use of this service in the desktop version is annoying due to the constant updates which lead to reinstalling the application. If they could give support with updates on the same downloaded version, it would be great.

I like the payment model. For the people who need to create, they buy their licenses. Everyone else can use the free Tableau Viewer. This is much better than some of the competitor products, which require full licences for everything.

I have trialed a number of different tools similar to Tableau. There seems to be a whole group of them. However, I found that Tableau was by far the easiest to use. Within about 20 minutes of playing around I was able to quickly make fantastic looking, incredibly useful charts that I struggled to make in Excel or other data discovery tools.

I have only trialed it. I could not get this product signed off due to budget constraints, not related to Tableau (which is far from the most expensive out there). 

Recommendations to others considering the product: Trial it and play around with it. You will be amazed at how quickly you pick it up. 

I have been using Tableau to visualize data sets. The three features that are most valuable to me are:

• Ease of use. Most of the configurations are accessed by drag and drop, so very little actual programming is required.
• Interactivity, especially the ability to use tool tips to identify exactly which points are plotting in an unusual or unexpected position. This is the first step in distinguishing outliers from important data features, which is an important part of data exploration.
• The ability to easily annotate and export finished plots for presentation purposes.

I have previously used Excel or R to perform exploratory data analysis. Tableau is easier and quicker, which means results can be obtained more quickly.

Some of the command choices have to be memorized and are not intuitive. It could be even easier to learn.

I have used it for about three months.

No issues with deployment, except I wish a version was available for Linux (Ubuntu).

I haven't needed technical support yet.

I previously used R for data exploratory analysis. I'm choosing Tableau because it is quicker, and exploratory data analysis by its nature requires a large variety and volume of output.

Initial setup was very simple; standard Windows installation.

Just me... No problems. Just note that Tableau workbooks are stored in their own file structure by default, not in the file where the data originated or where the exported charts are stored.

Tableau has a free trial, free versions for academic scholars/faculty, and a free public version. The paid versions are a little pricey, but likely worth it.

There is a public version you can implement for free. Its main restriction is the variety of data source connections that it supports. You can still work with the typical text or Excel files, but live database connections are not supported.

I think it's great at what it tries to do.

I really like the design of the charts. The rapidness of the development is impressive. Its full set of options helps you reach the specific chart that you need and you can add any kind of additional data source (Excel, flat file, databases) at any time.

In comparison to others, this product gives you the power to make any chart that you can imagine with your data, getting insights with the results and leveraging the need of a “metadata” model behind it.

With the rapidness of the development, the business user only needs 1/5 or maybe 1/10 of the time required to perform analysis and achieve results; they can just use drag & drop.

The most important and valuable feature is the ability to merge any kind of data with your data set, even cloud data (web services). It gives the business user the power to analyze something new with his own datasources.

My company is a Tableau partner, and we are located in Lima, Peru. We used it to perform a geo-spatial analysis of prospects, and we created a distribution of them with a drill-down analysis for future clients, so we can segment the appointments and the demo presentations.

Tableau lacks a lot of ETL capabilities. Of course, it’s not the core of the product but it is the best tool for data discovery and really needs an ETL or data quality module inside of the suite. Enterprises have to use another tool (such as Alteryx, IBM DataStage or Talend Studio) in order to support some business needs. But this entails additional cost, maintenance, resources, etc.

Tableau will add a lot of capabilities for data blending, joins between different data source, etc., in its next version, Tableau 10.

I have been using Tableau Desktop for three years. I began with version 7.0.

Tableau is easy to deploy.

Stability is great.

Scalability lacks some features. For example: governance, better clustering, dual authentication, detailed options of security, events manager, etc. That is why I only see Tableau as a data discovery and dashboarding tool (for senior management).

Support and customer service is good, not excellent. 8/10

I was using SAP BusinessObjects for four years, then I met Tableau and I realized how discontinued the SAP product was. Of course, all the BI platforms think that way, they were discontinued with the monolithic vision of data warehousing.

Then, all of the data-discovery tools appeared and all of us were amused.
I chose Tableau because it can give you answers very fast without the intervention of IT (most of the cases).

As we can see in the Gartner Magic Quadrant for Business Intelligence and Analytics Platforms, Tableau is the leader among all the data-discovery tools, Tableau defined the BI trend, and now the rest of the BI platforms are incorporating these functionalities and improving them.

Initial setup was easy, the commercial department of my company adopted the tool right away and start creating its dashboards.

We implemented this with an in-house team. We used the product portal in order to learn about its development and we used some classrooms in the region for Sales, Tableau Desktop and Server.

Tableau offers a rapid ROI in comparison to other tools. It’s a very cheap tool, but it has some barriers in big enterprises.

They should read about compatibility. Before implementing Tableau, they should meet with the business users and ask:

• What are your needs in business intelligence?
• Do you have some information silos?
• Is the generation of information a manual process?

The BI area should perform a self-assessment of a business intelligence roadmap in order to plan the development of the product, the areas involved in the pilot, the information needed to achieve the business goals and define the final architecture for the BI deployment in the near future.

We use Tableau for the all kind of dashboards.

Tableau as a BI solution provides a platform to develop user-friendly, story telling dashboards, which provide insights to help management take decisions.

The solution has a lot of customization when comparing to Microsoft BI.

The customization requires a lot of effort and should be simplified. The performance could be better. When comparing the performance of Tableau to other solutions, such as Microsoft BI, they are not as good.

I have been using Tableau for approximately four years.

The stability is very good.

Tableau has good scaling capabilities.

We have approximately 30 to 40 users using this solution in my organization.

The support is good for Tableau. However, if we ask for a certain feature they will not entertain us, unless other customers are also asking for the same feature.

Positive

We previously were using Microsoft BI and we switched to Tableau because of the increased level of customization it provides. Microstrategy can also be a considerable alternative.

The installation is complicated and took us approximately four hours.

It would be best to use an integrator or other professional assistance for the implementation.

We have approximately two engineers that handle the maintenance of the solution.

Our management can take decisions based on insights provided by Tableau, which are smart and help us reduce costs and data issues.

There is a license for the use of this solution and it is on a per-user basis. The server is free but the users you have to pay for.

We performed a POC before going with Tableau, we tried Power BI because Power BI is competing against tableau. But to use Power BI at its full potential, you need the Power BI cloud edition, which our organization cannot go with. So the obvious choice was to go with Tableau.

Tableau is very good, but customers have to understand the requirements of hardware and software the way Tableau works. If they have some requirements that Tableau cannot meet, they will understand how to do it in an alternate way.

I rate Tableau an eight out of ten.

When we work with CXOs to create dashboards we use Tableau. C-level employees like a CXO, a CEO, a VP, prefer to work with Tableau. It's easier and better for them.

For Tableau, the most valuable feature is the user experience and the quality of the end product.

One thing I would want to change for Tableau is to have a lower-cost model. It's pretty high for enterprise deployment.

In the next release, I would like to have the capability to call machine learning models within Python while I'm building a dashboard. The value calculation should be a machine learning model, which is running somewhere else, on say, Amazon. These tools give good outputs, like calculated fields and all. But today the outputs are not straightforward. In simple terms, I need machine learning on the fly. That is not there.

I have been using the solution for four or five years.

I would say the solution is very stable. We have not had any issues in using the product at all.

The solution does have scalability issues. When the data size increases, the product slows down and doesn't work right. In addition, it's very expensive to scale.

The only other solution we use and have explored is Power BI from Microsoft.

The solution deployment was pretty simple and straightforward.

We deployed the solution with our in-house team.

It's an enterprise solution, and we have all licenses. Tableau has multiple licenses; there is a reader, a developer, and an administrator.

If there are 50 or 100 users wanting to use Tableau, it's pretty expensive. The license is very expensive. We have 20 to 30 users in our company.

Because the solution is a drag and drop tool and what unique features we need or what we want to build, we cannot build using the tool. So we use JavaScript for that. We write our own code and build our own solutions.

My advice would be that all solutions are good, but it depends on your use case. If you are building something for C-level employees, use Tableau or another solution.

I would rate this solution an eight out of ten.