Tableau Reviews

I'm collecting some information and some reports from SAP and sending them to users as a graphical report. That's basically how I use the product.

The new pre-built application of Tableau is amazing.

The initial setup is simple.

It's a very stable, reliable solution.

You can scale the solution.

The dashboard has a lot of great options. 

I'd like it to work without the workflow or pushing options from the build, every time you need to do a refresh. We need a workflow for pushing the data to the cloud or to the server when you are using the pre-built application, the new application.

In the cloud sometimes the performance is a little bit slow.

I've been using the solution for two and a half years.

The stability has been good. It's reliable. There are no bugs or glitches. It doesn't crash or freeze. 

I have found the solution to be scalable.

At my organization, we have about ten to 15 regular users. 

We use it pretty extensively - at least once a week.

I'm not sure if we actually have plans to increase usage at this time. 

So far, I haven't needed any help from them. It's a good application in and of itself. I haven't needed technical support.

I used a little bit of Power BI. I know Tableau better, so I moved to Tableau Arabic.

The initial implementation process was straightforward. We did it without any problems.

Since the solution is on the cloud, you don't need a lot of staff for maintenance tasks.

You do not need an integrator or consultant to assist you in the implementation process. We were able to do it ourselves. 

We have a standard license that we renew yearly.

I'm an end-user.

I'm using the latest version of the solution.

I'd recommend Tableau to others. It offers good performance and the dashboard options are solid. 

I'd rate the solution at an eight out of ten.

Valuable features include the various “Show Me” graph options; the ability to do forecasting (which is an area that Tableau needs to continue growing its modeling capabilities); and the immediate responsiveness to adding dimensions/measures and their effect on the visualization.

We have used Tableau to develop institutional dashboards for the university. We’ve used it to illustrate trends in cash balances, research grant expenditure trends, and student metrics and performance.

I’d like to see the forecasting capabilities expanded from an algorithm standpoint to offer different options for multi-variate forecasting. I think they can improve the ability to integrate with web pages. I’d like to see a more secure option for data regarding HIPAA regulations.

We’ve been using the Tableau solution for over three years. We started out with about 30 users and have grown to over 350 interactors and 50 authors.

A strong guide to help determine the scaling up options does not exist; it is still new to third-party support consultants which performance options are the best. I do like the fact that AWS has a one-click solution, but it needs more of a config wizard to better outline what storage/memory impacts choices will produce.

We have experienced less-than-preferable service with the technical support. For a while, it felt like they were experimenting for answers, even with complete log and infrastructure details. Their response time to issues is not acceptable for customers who are paying for core licenses, and they acknowledge that.

Initial setup was straightforward; the upgrade path is also straightforward.

We implemented from within our team. We did engage with a consultant about two years later to see how we were doing and discuss the next steps with server admin training. The results were acceptable.

Pricing continues to be a sore spot. Desktop licensing discounts in bulk do not exist, which is challenging for a non-profit. Server core licensing is also prohibitive from an expansion standpoint.

We only went with Tableau based on the feature set and the user base reviews.

There is a lot of competition brewing with other visualization providers that may be at better cost points. Definitely go in and deep dive/experience the other solutions. Though Tableau has a great reputation for ease of use, there definitely is a learning curve to optimize it, and other solutions like Microsoft Power BI and Qlik are making progress.

It's similar to what we do with Power BI. It is used for dashboarding as well as a few analyses.

When compared to Power BI, Tableau has more readily available resources. In any kind of material, learning material, or if I find a new chart and decide I want to do it, Tableau is more easily available than Power BI.

It's a little more complicated than Power BI.

More visualization options, but not the same as in Power BI, where there are simply more options. I see very few options here. Many of these must be customized and custom-built, which is a lengthy process.

I would like to see more options in visualization customization.

People are migrating to Microsoft BI due to the speed, which is quite slow to load, and the lack of visualization options. There are a few default options in Power BI that Tableau does not have.

I would like to see the added visualizations and possibly an easier way to process data, which are useful now that we all have Power BI, there is a whole power query interface that directly links to Microsoft BI, whereas with Tableau, I would have to go through an entirely different process for it.

I have been using Tableau for one year.

We use the latest version.

It can be deployed both on the cloud and on-premises.

Tableau is very stable, but it takes too long to load.

Scalability has been fine. So far, I believe it has served our purpose.

We have more than a hundred users in our organization.

It is being extensively used, but it is getting to be lesser now.

We have also used Power BI.

We found Power BI to be more useful than Tableau.

Tableau was already set up when I arrived.

It is purely a visualization tool, as opposed to Power BI, which has connectivity to the entire Microsoft product suite, including your Excels and other tools, which Tableau does not.

I would rate Tableau, a five out of ten.

You can create many different types of visualizations and charts, ranging from simple to highly advanced. And if you're doing advanced analytics, you can leverage Tableau by integrating it with other solutions. You can also do a lot of automation in Tableau, and collaboration is quite good too. 

They currently don't have a great Workday connector. Right now, Tableau can connect to more than 80 different types of databases or data sources, but it's challenging to connect with a few types, like Workday. So if they can come up with a better version or a connector for Workday, it will solve a lot of problems.

I've been using Tableau for around five years.

I can say Tableau is highly scalable. Now that they've introduced Hyper, you can create an extract of more than 5 million rows in minutes and then do your analysis. So that's a very optimized way to analyze a lot of data. That's why many other companies like Amazon use Tableau to create their visualization, reports, and charts, considering that their data volume is very high. 

Tableau technical support is quite good. The Tableau community is also helpful. 

Tableau's pricing structure is unusual. So let's consider all the other competitors in the market. For example, we have products like Tableau, Power BI, Cognos, and QlikView in the data visualization segment. Compared to those, Tableau is quite costly. Their desktop version is expensive, and if you're using their servers, it's even pricier. Of course, they give discounts to bigger organizations. For example, we are premium customers to them, so we are getting it at a different cost, but for an individual, it's costly.

I rate Tableau nine out of 10. I would recommend this to anyone who is coming into the data analytics space. 

I've used it for multiple purposes, for example, for exploratory analysis or just for dashboards for presentations.

I'd say it brings a centralized place to check day-to-day metrics and KPIs. It helps reduce the duplicated reports or sources of information to get the same data or information. Everyone knows that those dashboards are up to date. They know where to find the answers they're looking for.

I really like the interactivity of the dashboards.

I appreciate the fact that you can have filters and parameters so that users can really customize the view to what they want to see.

Truthfully, this solution offers pretty much everything that I need for my everyday tasks.

It seems that power BI is more targeted for report creation while Tableau is more of just a dashboard. If you need to have something report-like, or downloadable to share outside of the dashboard, that's where Tableau is lacking some features. 

Users would like to be able to export an Excel file when they see a table or something like that. That's not an out-of-the-box feature for Tableau.

I've used the solution for a year and a half so far. It hasn't been that long.

I've had a good experience with the stability. There are no bugs or glitches that I have experienced. It doesn't crash or freeze. It's reliable. 

We did have an issue with our server and it took a while for Tableau support to find a solution. However, that was a one-time thing. That's the only time where we've had issues with our server.

The scalability is pretty good. In our case, we did start small and we are now scaling in for our different departments. It's working great.

We are not a big group, however, I would say that we have around 80 to 100 users and that combines creators, explorers, and viewers - a little bit of everything.

We are getting used to it and using it more and more. We are expecting to increase usage in the future.

I've never been in touch with technical support. I cannot speak to how helpful or responsive they are. 

We did not previously use a different solution prior to adopting this product.

I wasn't around for the initial setup. I cannot speak to what the process was like and couldn't say if it is difficult or straightforward. 

We have some server admins that take care of it and work with Tableau to support it whenever needed. It's a group of people, however, I am unsure about the actual number of personnel that handles it directly. It might be three to five people. 

I've looked into Microsoft BI and downloaded some information about it recently.

I'm just an end-user of the product.

I'm likely using the latest version of the solution. 

Everything was implemented when I started, so I wouldn't know if there were any hiccups or best practices, or lessons learned from the process of setting it up. 

I'd rate the solution at a nine out of ten, from the experience I've had so far. It has helped us tremendously with our everyday reporting and things like that. I can do pretty much everything I want to do and it's been working fine for us.

Tableau has improved my organization in a variety of ways, one of its uses being that of data analysis. It provides a server platform for sharing information. We use it for internal collaboration, as well as other tools for data catalog, for creating the dashboards, for preparing the data in preparation of creating the dashboards, called an ETL extract, and as a tool to transform and load. Tableau is a platform that has several products, perhaps four or five, that average for the fifteen of big data, data evaluation and data collaboration. No specific aspect can be used for this and it can be employed in marketing and finance. It serves the needs of data analysis and providing an algorithm for machine learning. For instance, you can have a logistic regression to analyze whether a specific customer is a good bet or not, such as a bank that is contemplating the loan of money. It allows you to visualize and analyze your data no matter what it may be, though it can be used for an alternate solution.

A feature I have found most valuable is the ease of use and straightforwardness, in addition to the flexibility of Tableau. I like the fact that Tableau can connect to a wide variety of databases, be on cloud or on-premise. Tableau can connect to over 100 database types, including structured and non-structured databases. Tableau can connect to a PDF and extract all the tables you have in that PDF. Suppose you have a one hundred-page PDF containing sixteen tables of data. Tableau can connect to that PDF and extract its data. Tableau can connect to Google Drive, to a host of marketing portals on the internet, to cloud companies such as AWS or Alibaba and to many different types of databases. That's one huge advantage of the tool.

While it can be complex if you need to alter a lot of parameters, it provides simple installation. It is very easy. All you would need to do if you have only one Tableau running server is to employ the maximum connection and install a license column in Adobe Reader. 

An area needing improvement involves the complexity of the product should you need to alter a lot of parameters. 

Definitely speaking, it's straightforward and it's very easy. Implementation problems can be dealt with by the client, in place of the user consultant. Let me give you some examples of things that could take long in a Tableau implementation. Suppose you have five different business areas in your company: marketing, supply chain, finance, HR and procurement. Let us suppose that access to HR salaries is not company-wide but is limited to only a select number of people in HR, such as the manager or the director of the department. Yet, I want people in the supply chain to be able to see and access different data from different areas. While this would not be technically difficult it would be time consuming if the businesses are very particular. There may be many policies involved in access authorization, in data availability and the like.

This can involve a very strict security process using an outside identity provider. Instead of just logging in your username and password, you may have different technologies which are more safe and secure that need different providers to interface in Tableau. Depending on the need, this will be time consuming. For instance, while I don't know how this would be in your country, suppose you have an identity provider, in Brazil, marketing in Tableau. If you go to Asia, you may sometimes have a bio-metric identity that your hand or fingers employ which is going to get back at you. In that circumstance, they are going to send you a number or a code in your cellphone, requiring two steps, one to enter the bank and the other to withdraw your money. So, these things we call an outside identity provider, meaning a different vendor or different companies who manage the servers of managing identities. These would entail an integration with Tableau and these outside companies for security purposes. This would involve them sending me files and me sending them back in order to authenticate the user into the Tableau server.

This can be time-consuming because they involve or require a different partner. Tableau is made for basic needs, such as requiring a user and a password to log in to the server; an unsophisticated architecture; or use of a single instead of a cluster of servers. If you have non-specific data security needs or you just want to analyze and sell data, that can take less than a day. But if you have technical servers, many interfaces, different providers and more serious processes, that will be time consuming. 

While Tableau does integrate with Arc server and Python server, the integration process is slow and the information is integrated in a protracted fashion. Sometimes your data will vary. You may have a vector of data. You may have a matrix of data. For some algorithms we do not use regular data, but a different data structure. Tableau does not work with these different data structures. As such, interfacing with Arc server and Python server, which are still languages that are widely used in machine learning, all happen slowly. It does not happen by a matrix of data and data vector. 

I have been using this solution for five years. 

In the past I worked with Oracle E-Business Suite while working with ERP markets over a thirteen or fifteen year period. Yet for the past five years I've been focusing mainly on artificial intelligence, machine learning, big data and the use of other software, such as  Tableau and Azure for the purpose of developing and building data to create algorithms and visual dashboards to show the data. It's been around five years since I have turned my focus solely to big data and machine learning. 

Definitely speaking, the initial setup was straightforward and very easy. 

Another option I evaluated is Power BI from Microsoft. It's cheaper than other solutions and requires fewer different packages. The major competitor of Tableau is Power BI from Microsoft and Microsoft's much cheaper than Tableau. But Microsoft usually requires me to be on Microsoft cloud Azure. You have to buy other solutions for an integrated solution. At the end your cost will be much higher. So Tableau is more flexible. 

In Tableau, I can have a scatter plot with millions of marks. Suppose I have a graph that plots my value against my process and each dot in the graph is a sale that I've made. So I have 30 million dots in this graph reflecting my 30 million sales. Tableau can run this easily and fast. Power BI cannot. Power BI has a limitation of 13,500 marks, meaning Tableau has more capacity in delivering data than its competitors. 

It’s good for quick visualization and being able to quickly consume unstructured data to play around with. This is good way to show a demonstration/prototypes of dashboards and scenarios for design discussions on reporting requirements or to show what the data is telling us when it comes to features of data integration, OLAP services, data mining and extract, transform, and load (ETL) capabilities.

Good for adhoc visualization of an unstructured dataset which comes from other sources outside of source systems that you can overlay on top of the structured data and you have to get a quick visualization dashboard prototype going. It helps with the Agile design build and can be used in our current operations analytics work to overlay multitude of data sources that we know of. Can always work offline, which is nice. It’s good for organizations with very limited staff to do quick report builds and dashboards that can be put on our SharePoint site for sharing or on reports when responding to data caps. I use it a lot for design discussions so I can communicate the gaps in data sources for data exchanges or to generate a storyboard prototype of how the data is to be used in visualization but where we need to have data exchange/ETLs on.

It is good for its use if ad hoc, offline, or needed for quick turnaround on reports/dashboards. It is not so great when it comes to data exchange/integration, data mining, etc. I rely on what’s available in current versions to see what APIs and plugins that I can use and they have Open Source on GitHub is a plus to share things to re-use.

Room for improvement is more on data integration features that are agnostic to any solution platform but can be plug and play to be able to reuse what was built out Tableau in any other platform of work.

Over five years, and the past three more for integrating the use of a similar family of tools where Tableau is one of a few options in our environment, where these services are considered for quick-hit items as needed, given time, dollars, and analyst skills.

No.

Yes, see other answers. Scalability per user defined elements are okay but not so much for enterprise wide reuse. Per license cost can have some work done to it to make it more affordable on the recurring maintenance end of things. I would like to see more subscription based models.

I don’t have to use it much since I can get much of this through current site materials and social media blogs/videos.

I didn’t switch. It was just a matter of seeing where Tableau makes sense as a service to use in our environment, which is for the simpler, not so complex, but quick turnaround. Worked with other technology stacks that are similar, like Information Builders, SAP, Microsoft, Oracle, SAS, MicroStrategy, IBM, Salesforce, Qlik, etc. I find Tableau the easiest on visualization and its license model straightforward. But when it comes to scaling to other interoperation work, not so great on the wizard template, to do data mining/exchange. It doesn’t have that robust analytics and intelligence self-learning feature that comes with other tools.

It’s straightforward, like any typical software. You have just got to understand what the various versions of API and plugins and what they can do. Though I have noticed that there were situations where it was said it was able to do things, but not until a later version. It needs better communication on that front.

License small scale and run with it to get a business case going on its use. Give the licenses only to those analysts you want to do quick turnaround visualizations and those that know the data sources/data (those that don’t will just have access to tool and that compounds a problem with giving you something nice to look at but no meaning behind it, which I wouldn’t recommend). Look to existing platforms of one’s current BI environment and see if you can have a server license which can reduce the per user licenses.

I wish there was more of a subscription model with the pricing when it comes to Tableau, so you can get all the latest version upgrades/features if you pay monthly/annually, rather than buy straight up licenses that you lock to a baseline version and have to pay for upgrades later on. It limits how many users you can get on the thing, and it's not like you will use it all the time.

Yes, we did an alternatives analysis of all the product line options against our criteria of need in our environment, where recurring cost, time to implement, and other interoperation, security, platform scalability, architecture, etc. factors play a role. The majority were mentioned above.

We always have the latest versions of Tableau (part of the package deal), so we can have the latest in APIs and integration hooks and plugins needed across our platforms of OBIEE, SQL, etc.

Tableau is good for quick visualization once you have the data, but not such a great interoperable tool or getting to multiple sources without a lot of work and know-how. Good for pulling in unstructured data and doing quick reports/prototypes. Does require some stronger business analytical skills rather than your novice user (and technical with regards to use of API and plugins).

If new to the analytics/BI market, use it, as it's good for getting you jumpstarted to understanding your data/data sources and to envision what you can use the data for. It's a good starting tool for that. If more advanced or need it for interoperation, I suggest looking to see how it fits with your current environment and determine where best to use it as it shouldn’t be your only option as the features are not robust enough to scale for everything.

The drag and drop in development, design and usage; the Show Wizard feature.

As a BI and data visualization enthusiast and provider, I have compared Tableau against other BI and data visualization tools. It provides tremendous ease of use and a shorter learning curve when compared to the rest. Provides astonishing visualizations as well.

The user interface and ease of use requires a bit of a learning curve to pick up. No drag and drop functionality at the development stage, unlike its competitors.

The data preparation is quite good but not as powerful as the one I use or would recommend for data manipulation and cleansing as well. Tableau seems to focus on the data visualization end and provides, or has partnered with, some other software for data preparation.

Three years.

None at the moment.

Tableau, as noted above, does not provide much in terms of data preparation. Handling of large volumes of data sometimes does not work well with this all-in-one purpose tool making it less ideal for business users.

The Tableau online community is rich and vibrant and provides quick guidance on getting started with the basic use of Tableau.

None.

The initial setup is pretty straightforward for personal use, except when looking at deploying on local premises. Doing so entails some configuration during the installation process.

Tableau pricing and licensing is on the high side for a small company, but it’s competitive among its peers. They offer a monthly subscription for their cloud service.

As a consultant in the area of Business Intelligence and data analytics, I have personally evaluated BI tools such as QlikView, Qlik Sense, Power BI and MicroStrategy.

Invest in the memory and RAM of the PC or server you intend to use with Tableau. Though most database sources are available for connection, you should still ensure you have all the necessary resources and connectors installed for proprietary databases.