Spotfire vs. Tableau Server

Spotfire was used to look at a large data set of an in process manufacturing step. The data visualization was set up to look at yield as a function of several inputs (chemical / equipment / operator). After only a short analysis it was immediately obvious that there was a 5% yield discrepancy based on the operator using the equipment. The operators were retrained and the yield gap was eliminated.

Incentivized

Tableau Server is well suited for a data warehouse build and handling big data. Tableau data aggregation, transformation, clustering capability is powerful and easy to implement. The choice of charts and visualisation tools is outstanding. Customisation and dynamic data visualisation capability is superb. The user interface takes some time getting used to.

Incentivized

• It has the best coding integration (python, R) of any BI product
• The ability to work with very large datasets (10 mil+) is better than competitors
• Export options are more complete and have better functionality
• The data canvas is the best tool to join and transform data vs. competitors

Incentivized

• It's good at doing what it is designed for: accessing visualizations without having to download and open a workbook in Tableau Desktop. The latter would be a very inefficient method for sharing our metrics, so I am glad that we have Tableau Server to serve this function.
• Publishing to Tableau Server is quick and easy. Just a few clicks from Tableau Desktop and a few seconds of publishing through an average speed network, and the new visualizations are live!
• Seeing details on who has viewed the visualization and when. This is something particularly useful to me for trying to drive adoption of some new pages, so I really appreciate the granularity provided in Tableau Server

Incentivized

• They should have a lower price point for users to access the analyst version who don't require advanced capabilities. For example, a lower price if users just need to do some basic slicing and dicing with their data and not have to the data science functionality (ie. K-means clustering, regression modeling, classification modeling, etc.).
• Currently, you can't change the font type/color on the axis, which I'm sure will eventually be available in the future as they have a Spotfire Ideas portal that they're fairly responsive to and act on. I guess at the end of the day, it's about the data and what insights you get from it.

Incentivized

• While it took little time for our data analysts to crank out visualizations, it did take some time(longer than I expected) for our technology operations team to configure the server to share the sizes.
• The server update process is rather cumbersome -- requires a full uninstall/re-install.
• Again, while it took our data analysts next to no time to start creating, I've been in other organizations that have struggled with the feature-rich interface and complexity of the Tableau client. So, it requires the right personnel, with dedicated time, to fully leverage the tool.

Incentivized

It's a very powerful tool that allows for a myriad of customizations within the analysis files themselves, particularly with the custom expression functionality. There have been some great strides with the quality of the visualization options (which were not great to begin with) and I hope to see more improvements made as the product gets updated.

Incentivized

It simply is used all the time by more and more people. Migrating to something else would involve lots of work and lots of training. The renewal fee being fair, it simply isn't worth migrating to a different tool for now.

Incentivized

Basic tasks like generating meaningful information from large sets of raw data are very easy. The next step of linking to multiple live data sources and linking those tables and performing on the fly analysis of the imported data is understandably more difficult.

Incentivized

User experience is the most important factor to consider whenever considering capabilities for non-technical business users. If the learning curve is so steep business users must be advanced users to be productive, you hit the wall of diminishing returns, this is exceptionally true when it comes to analyzing data. Transforming data analysts into BI development experts shifts the focus of the analyst from analyzing data to mastering software. Tableau does a masterful job at minimizing the technology and maximizing the users understanding of their data.

Even though, it's a rather stable and predictable tool that's also fast, it does have some bugs and inconsistencies that shut down the system. Depending on the details, it could happen as often as 2-3 times a week, especially during the development period.

Our instance of Tableau Server was hosted on premises (I believe all instances are) so if there were any outages it was normally due to scheduled maintenance on our end. If the Tableau server ever went down, a quick restart solved most issues

Generally, the Spotfire client runs with very good performance. There are factors that could affect performance, but normally has to do with loading large analysis files from the library if the database is located some distance away and your global network is not optimal. Once you have your data table(s) loaded in the client application, usually the application is quite good performance-wise.

While there are definitely cases where a user can do things that will make a particular worksheet or dashboard run slowly, overall the performance is extremely fast. The user experience of exploratory analysis particularly shines, there's nothing out there with the polish of Tableau.

Support has been helpful with issues. Support seems to know their product and its capabilities. It would also seem that they have a good sense of the context of the problem; where we are going with this issue and what we want the end outcome to be.

Incentivized

I think the folks that work in support are generally pretty good at what they do (when you get them on a WebEx). But the process of reporting issues to them and waiting for a response (via email only) is a hassle. I never understood why you can't just call them up and discuss the issues with them. It would take a handful of email exchanges before they would agree to a WebEx session. That was frustrating.

The instructor was very in depth and provided relevant training to business users on how to create visualizations. They showed us how to alter settings and filter views, and provided resources for future questions. However, the instructor failed to cover data sources, connecting to data, etc. While it was helpful to see how users can use the data to create reports, they failed to properly instruct us on how to get the dataset in to begin with. We are still trying to figure out connections to certain databases (we have multiple different types).

Incentivized

In our case, they hired a private third party consultant to train our dept. It was extremely boring and felt like it dragged on. Everything I learned was self taught so I was not really paying attention. But I do think that you can easily spend a week on the tool and go over every nook and cranny. We only had the consultant in for a day or two.

The online training is good, provides a good base of knowledge. The video demonstrations were well-done and easy to follow along. Provided exercises are good as well, but I think there could be more challenging exercises. The training has also gone up in price significantly in the last 3 years (in USD, which hurts us even more in Canada), and I'm not sure it is worth the money it now costs (it is worth how much it cost 3 years ago, but not double that.)

Incentivized

The sales consultants do an amazing job of introducing the tool and its capabilities. They are also helpful in explaining the layout of the desktop client and its different functionality. Keep in mind that they use a sample data source (MS Excel) with a very small amount of data to show off what it can do. What you have to remember is that you are buying the tool so that you can connect to large amounts of data (and possibly blend data together from different databases).

The original architecture I created for our implementation had only a particular set of internal business units in mind. Over the years, Spotfire gained in popularity in our company and was being utilized across many more business units. Soon, its usage went beyond what the original architectural implementation could provide. We've since learned about how the product is used by the different teams and are currently in the middle of rolling out a new architecture. I suggest:

• Have clearly defined service level agreements with all the teams that will use Spotfire. Your business intelligence group might only need availability during normal working hours, but your production support group might need 24/7 availability. If these groups share one Spotfire server, maintenance of that server might be a problem.
• Know the different types of data you will be working with. One group might be working with "public" data while another group might work with sensitive data. Design your Library accordingly and with the proper permissions.
• Know the roles of the users of Spotfire. Will there only be a small set of report writers or does everyone have write access to the Library?
• ALWAYS add a timestamp prompt to your reports. You don't want multiple users opening a report that will try and pull down millions of rows of data to their local workstations. Another option, of course, is to just hard code a time range in the backing database view (i.e. where activity_date >= sysdate - 90, etc.), but I'd rather educate/train the user base if possible.
• This probably goes without saying, but if possible, point to a separate reporting database or a logical standby database. You don't want the company pounding on your primaries and take down your order system.

Implementation was over the phone with the vendor, and did not go particularly well. Again, think this was our fault as our integration and IT oversight was poor, and we made errors. Would they have happened had a vendor been onsite? Not sure, probably not, but we probably wouldn't have paid for that either

Spotfire is appropriate for every organization of any size because it can be a recipient of data for better decision-making. Being a robust development platform for creating reports and dashboards, creating a new Spotfire dashboard is relatively simple. Developers can create highly customized dashboards using the tools it provides. I will recommend this software to others

Incentivized

Looker and Tableau are quite similar products. I think Tableau's ability to view data visually is more comprehensive. The different breakdowns in UTM level versus first touch and last touch are shown in a visual format, making it much easier to view and interpret the results. Tableau also has faster load times compared to Looker for larger datasets.

Incentivized

In an enterprise architecture, if Spotfire Advanced Data services(Composite Studio),data marts can be managed optimally and scalability in a data perspective is great. As the web player/consumer is directly proportional to RAM, if the enterprise can handle RAM requirement accomodating fail over mechanisms appropraitely, it is definitely scalable,

Incentivized

• Spotfire really helped a lot of people in terms of analysis. It eliminates data analysis in excel. Because even underlying data you can explore it in Spotfire.
• Spotfire helps data analysts to investigate data and also help analysts solve inconsistency of data.
• Spotfire helps data analysts in building great dashboard that provide insights to users to make decisions to drive revenue and manage the churn.

Incentivized

• Tableau Server has had a huge positive impact. It has allowed us to quickly distribute complex dashboards across the company
• Tableau Server has allowed us to easily manage our entire employee base at the company and control the dashboards they view and interact with

Incentivized