Tableau Enterprise Reviews

The feature we've found most valuable is Data Extract, which extracts a local copy of all required data in a columnar format store. It does in-memory processing which is lightening fast.

It placed the power of dashboards and scorecard development in the hands of business people, so there's less dependency on developers.

They need to make it more flexible for enterprise administration, e.g, more job scheduling flexibility, more robust permission control, and more comprehensive mapping service that is native and not dependent on a third party like Mapbox. They also need to develop more comprehensive DR and HA solutions.

I've been using it for over three years.

It's excellent for deployments and upgrades.

We have had no issues with its stability.

We have had no problems scaling it for our needs.

They have good customer service support, although they do not always solve the issues. Also, sometimes support takes too long to find the root cause or a solution to an issue.

We previously used Cognos, and Microsoft BI. We chose this due to user-friendly structure. There aren't too many components to manage and understand like in Cognos or Microsoft BI, etc.

The initial setup was straightforward -- very easy installation and upgrades cycle.

In-house - very easy to implement in-house, just follow the installation and upgrade guide check-lists and first try on test environment before doing a production installation or upgrade.

ROI for Tableau when compared to other BI tools we have is excellent.

Tableau has both core-based licencing (for higher number of consumers scenario) and subscription based licences (for limited users scenario) - chose appropriate licencing based on your estimate of number of users.

It's very user friendly and its self-service approach helps business users to develop dashboards in no time. The learning curve is very short - lot of learning resources available.

Still need to do some catch-up on enterprise administration and Mobile friendly reporting e.g Android App is not yet available - expected to be released 10.0.

Tableau releases frequent major releases three to four versions per year, and monthly patch fix releases, so plan a strategy that you want to follow. We are generally one to two releases behind so we can keep up with them, and at the same time leveraging all new exciting features the release.

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.

Once you are comfortable with the product, building visualizations and dashboards is extremely quick.  I also have not seen a better geospatial drag and drop visualization tool out there yet.

It’s an excellent tool to quickly build visualizations supporting QA and data validation activities.

• Governed data discovery
• Collaboration
• Other enterprise features

We've used it for over two years.

We had no issues deploying it.

There have been no issues with the stability.

Older versions had trouble with performance when looking at larger datasets but it does not seem to be as much an issue now.

Sales support when we were first engaged with them was minimal.

There was no other solution in place.

It’s excellent for desktop analysis but make sure to include other tools in your evaluation if you are looking for enterprise support features.

The ability to make interactive graphs, tables, and maps that can be shared on social media, linked to, or embedded on a website are the most valuable features. The ability to allow readers to view and download the underlying data is another valuable feature.

I just did an analysis of real estate sales in my county (Bay County, FL) and it allowed me to share the results with the public in a way they can make their own discoveries beyond what I have presented. 

Tableau Public is free, which is incredible. However, the paid version is too expensive per user. They need to reduce the cost of the user that is not making the analysis, but only reading / drilling down on the results. It is hard to get a client to pay that kind of money to view reports.

From my conversations with Tableau, their product Tableau Online is what allows others to view and interact with data online privately. The cost per online user is $500 per year. There is a free Tableau Reader, but it is limited. So, if I wanted to make data visualizations for a client or within my own company, I would have to pay for the desktop software to make the visuals plus pay an additional fee for everyone who wants to use the full functions online. Tableau Public is free and an awesome tool, but it is all publicly available.

I've had no issues with deployment.

I've had no issues with stability.

I've had no issues with scalability.

• Visualization
• Data capacity

Where I'm working, we have many reports developed in Microsoft Excel to present results about the business. However, when we need to work a large volume of data, they are developed in Tableau because access to data from Oracle and managing large data volumes is easier than Excel. All the reports that we develop using Tableau are complimented by our directors, as the information is visualized well.

When we need to work with a large volume of data, we can create an extraction, validate data easily, and then present it to our users using Tableau Server or Tableau Reader.

I have difficulty working with many filters on the dashboards, and I'd like to see more options in the "Histories" section. QlikView makes better use of the dashboard filters.

We've used it for two years.

In some departments we chose to install Tableau Reader, but it's necessary to create a ticket to update the software for each new version. This process is not good as it disrupts our day-to-day functions.

I work with 4GB RAM and rarely I have a problem with it. My OS is 32 bits.

We've had no issues with scalability.

I always take support from Tableau's forums and communities.

We also looked at QlikView.

It's a great solution to present data, and our directors love to work with it.

It's easy to start using to deliver off-the-shelf visualizations. It makes it easy to share dashboards with a team. It's a comprehensive solution that can scale from desktop (analyst, developer) to server (large end-user audience) with small or no changes.

In my experience, its greatest achievement has been opening stakeholders' minds. It pioneered the self-serve trend (which may have social roots) where people "own" their data and IT is a service provider to ensure visualization content is based on robust data. Connecting to a massive number of sources (that can be blended in Tableau) has also contributed to this achievement.

It came at a cost. Developers end-up, many times, scratching their left ear with the right hand, in order to make visualizations more powerful, effective or appealing than off-the-shelf ones. The next challenge for Tableau will be combining ease of use for basic-to-mid level complexity design (self-serve, "power users") with flexibility and repeatable development in a corporate environment (professional designers), avoiding "hat tricks" or "cookbook" style.

Also, when building corporate dashboards, it may be challenging to gain the type of control needed without having to resort into some forum tricks or Zen-Master's advice. Workbook, connection versioning, and governance would be great for mid-to-large size organizations. Server-wise, having options to trigger alarms to an Administrator under certain conditions would also be an asset.

I've been using both Tableau Desktop and Server for four years.

No problems at all. Very robust and well documented (both Desktop and Server versions)

No problems, at least with the data sources I have used Tableau so far - MSSQL 2008 & 2012, Teradata RDBMS 14.x, and MSAS Cubes.

Tableau can scale to massive datasets without problems (I used a few, approximately one billion-row tables), provided a DBA is part of the team to fine-tune tables and views. The proprietary columnar database engine is very fast and robust.

It's great.

It's great, although forums are usually the first resource to get answers from.

I have helped customers migrate from MS Pro-Clarity and Oracle Hyperion.

Tableau is not a demanding platform in pre-set environments before rolling-out as long as tech specs are met. However, certain design decisions need to be made in advance to ensure good performance and smooth scalability on a Server deployment (e.g. permissions, standards, etc.).

I act as an implementation consultant.

Go through the exercise of planning short and mid-term to understand what the best licensing model is e.g. per Core vs. Named Seats, number of Designers, etc.

Understand your organization's profile. Do you have or want/need to develop power-users or will you use traditional IT developed dashboards in an intranet/internet? Although Tableau can fit both scenarios, the first option would be the most benefited one when compared to other solutions. Look into redefining the relationship between business stakeholders and IT, since the former will demand more consumable information for analysis instead of packaged reports.

The use is only academic, for the moment.

I've used it for six months.

No issues encountered.

No issues encountered.

No issues encountered.

I've not needed to contact them.

I've not needed to contact them.

It was easy to setup.

We did it in-house.

• BIME
• QlikView
• SiSense

Data Preparation - This is a huge plus for Tableau as so many users have to spend time preparing the data before using Tableau

• Data Interpreter
• Splits -
• Really helps the average user

Drag and drop analytics:

Tableau 9.0 has a new Analytics pane that provides quick and easy access to common analytic features in Tableau.

You can drag reference lines, forecasts, trend lines, and other objects into your view from the Analytics panel. It is now easy to edit, format, and remove the analytic items that you have added, so you can experiment with different techniques as you explore the insights your data has to offer.

Ad--‐hoc calculations:

Ad--‐hoc calculations make it easy to add and edit calculated fields for your analysis. Double--‐click an existing field on the Rows, Columns, Marks, or Measure Values shelf to begin editing, or

double-click an empty area on a shelf to create a new calculation. As you type, a list of auto--‐complete options appears in a dropdown list, making it easier to find and pick the right elements.

Instant analytics:

Instant analytics provides an interactive experience for comparing summary information about a subset of marks to all the marks in your view. For example, you can compare the average for a few marks to the average for all the marks. After you’ve added trend lines, reference lines, reference bands, or distribution bands to your view, select one or more marks to see the new analytical indicators appear for the selection in addition to the analytical indicators for the whole view.

Level of Detail (LOD) Expressions:

New expression syntax in the Tableau calculation language lets you quickly create calculated fields that compute at the specified levels of detail. LOD calculations help you compute at multiple levels of aggregation and make it easier to create fields for analytical comparison (such as cohort analysis and totals or Average across segments), simplifying calculations that previously took several steps.

It's both intuitive and complex/deep. For our organization, it's given us opportunities to provide both on-sight and on-line training. We now have an online training product that more than offsets the expense associated with days of training. With Tableau, our customers more analytical.

It even has a connection to R and SAS for advanced users.

Also, it has given us the ability to collaborate with the Tableau servers, which is robust and can handle tens of thousands of users.

Tableau Server can now scale for unlimited users Enterprise scale brings with it the need for Governance. Data sources and workbooks must be vetted before they are "out there" to see except for the intended content consumers

The basic design of Tableau has some features that could be modified.

* There is no need to have five (5) ways to add a new worksheet. Brevity is rewarded - new users have so much to learn that 2 ways would do the job

* How to render time - When performing analysis, no single issue is more important than time series data. Tableau uses visual clues in many places - When one uses the pull down option for time that could be visualized better as a continuum. those selections should be presented in green to be visually consistent. Those above in blue.

If you're making a structured, strategic purchase, make sure that you have a plan for professional training.

• Go slow and methodically
• You must consider size of the company and types of users
• Desktop Plus server users - understand the constraints on the backend, and make sure you have enough CPU power
• There's lots of free stuff on their website that's great for the average user.