JMP vs. Logi Info vs. Tableau Desktop

Many organizations have seen their analytical capabilities, and the results from them, plateau. Of these, we've observed, that most of them didn't appreciate that they could do (even) better. These companies should definitely consider JMP. Any company that is research-based can benefit from accelerating their research, learning more in less time, effort and cost, with JMP's tools. Basically, any organization that is hungry enough for improvement to seek out better ways is suitable for JMP. Those who are happy with their current performance are not likely to consider the changes, though they were not major impediments by our clients, required.

The pricing of Logi (per server core) is highly attractive for internal-facing use as we can control/predict how many visits we will get to our internal Logi webserver. The fact that the only license required is on the server means that all of our staff can use Logi Info-presented content without restrictions. The option of OEM licensing is also attractive and presents many future options, but will require much more licensing as the webserver will require more cores to handle the level of traffic demanded by OEM usage.

The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).

Incentivized

• Graphs are more detail-oriented and contain statistical inferences.
• Everything is drag and drop. Pretty much easy to use and handle and also to learn.
• Importing and exporting the results are easy and they can be attached with any other tool for processing.

Incentivized

• Flexibility and easy standup. Users can choose to create their own Logi application or do a "quick standup" by using design straight out of the box. Due to varied customer requirements, Logi allows the developer to address all needs.
• Great design studio. The studio provided with Logi to create and maintain your Logi app gives a lot of detail and examples to guide you along the way. The tool even includes some additional tools for the layman to assist with deployment or wizards to help you create more complex type reports that otherwise would require more detailed technical knowledge to create. Of course, you can still do anything you want by hand if that is what you prefer!
• Documentation. Logi's developer portal provides plenty of documentation and examples to get users going. Need to create a custom template that builds from a table rather than being hard-coded? Search the documentation and you will find examples to piece together to form your solution!

Incentivized

• The Visualizations graphics are really good and the color options help in designing attractive charts. They help to convey more information and can be made interactive.
• You can add filters with offer you to plug and play with values and understand different outcomes.
• You can drag and drop options while creating charts and dashboards. also it is a very fluid layout.

Incentivized

• Loading a large amount of data is very tedious as it takes a lot of time and it crashes very frequently.
• I dislike the limited options they have in terms of statistical models or analysis tools.
• Variable value designation is a big problem in JMP, the software fails to recognize the type of data when it comes to the numeric value.

Incentivized

• Support. Logi used to provide EXCELLENT support. However, they've changed their support model and no longer provide excellent help. I used to get problems resolved within 15-30 minutes. Now, it has gone down to 48 hour response time just to answer a simple question. In-depth questions can go on for days or weeks.
• Based upon the change in support, and the fact that we pay for 'unlimited phone support' in our annual contract, we are moving away from using LOGI as a tool for the future.
• Learning CSS and Javascript would make you a better LOGI developer.

Incentivized

• Formatting the data to work correctly in graphical presentations can be time consuming
• Daily data extracts can run slowly depending on how much data is required and the source of the data
• The desktop version is required for advanced functionality, editing on [the] Tableau server allows only limited features

Incentivized

I've mentioned this earlier, but the licensing agreements are very prohibitive. I work with a company where my role has become less and less doing my own analytics and more and more trying to help other people in that role. As we are bringing more people "up to speed" it's hard to justify licenses for 2-3 people when they aren't full time, Six Sigma black belts just looking at stats all day. A floating license option would make this a no-brainer, since these people could continue their other work and add JMP usage as they grow their skills, but this is not something JMP/SAS has offered.

Logi Info is a very outdated, archaic product that tries to build .NET / Java web apps using an obscure XML-based markup language to implement BI widgets, with a lot of extra CSS/JavaScript needed on your own to make it do the best things. There are many other better tools. It is not a BI tool, and as a web development tool it's not great either. I'd recommend getting some good third-party .NET BI library if you want your web devs to make the reports, otherwise use a proper BI tool like Power BI or Tableau, or even Logi Composer (formerly ZoomData before Logi acquired it.)

Incentivized

Because right now its the best option out there (disclosure: I haven't used Qlikview or some of the other direct competitors of Tableau). The big investment is in Tableau Server not desktop. For the cost of the license of Tableau desktop, its a pretty good deal. You can hook it up to pretty much any data source easily. You can easily share the visualizations with your team/colleagues easily. Tableau Desktop is generally easy to use for business users. But the more advanced stuff is better suited for a analyst or someone with a IT/CS background.

The GUI interface makes it easier to generate plots and find statistics without having to write code. The JSL scripting is a bit of a steep learning curve but does give you more ability to customize your analysis. Overall, I would recommend JMP as a good product for overall usability.

Incentivized

I am giving 9 rating because the Logi Info still needs to improve on the tutorials part and make it easy for the beginners. Otherwise, it's a very good analytics tool which offers more than 20 types of visualization. It's predictive analysis feature and easy to embed with technologies make it stand out in the market.

Incentivized

Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.

When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.

Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast

Incentivized

The helpful tips are great for new users. I am always able to find solutions to a tool I am working with through the hep section. And my area has a users group that meets each quarter to share ideas and view upcoming JMP revisions.

Incentivized

The support process is bit slow and has a good scope improvement but overall it's good as team is very supportive. They generally take 1-2 days time to respond emails sent to them but some times a delay is also expected. Overall, I did not face any major issues using the service.

Incentivized

The Tableau Desktop's support team has been very helpful and tend to response very quickly. After all you have paid very premium price for the product and it goes to the services. This makes using the tool much easier for these who doesn't have such experience to get help quickly.

Incentivized

It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.

I have not used your online training. I use JMP manuals and SAS direct help.

I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems

Incentivized

Time needs to be spent ahead of implementation to make sure data sources are set up and ready. Consultants need to understand the data sources and the goals before setting foot on-site. Installation is easy, learning to use it takes time. The training resources available are great.

Incentivized

We actually use both JMP and IBM SPSS, but I think JMP's complexity lends itself to more in-depth statistical analyses. SPSS is designed for that as well, but we tend to use it more for quicker analyses, and we have found that JMP is far more powerful.

We test drove a lot of the big hitters, Pentaho, Sisense, Tableau, Jasper, Spago, Birt, Knime, Power BI and while most of them did a lot of things very well, but none did exactly what we were looking for without a lot of downsides (more developers, bolting on extra modules etc). Logi also was ultra competitive on pricing structure and they truly wanted to partner with us as much as we want to partner with them.

Tableau Desktop is clearly one of the best in the business. It has incredible capabilities, and many features are extremely useful. The intuitiveness of the dashboards and the graphical nature of the visualizations are widely used features and super helpful. One of the other benefits is that both programmers and non-programmers can equally explore and create their own opportunities, and seamless integration is possible.

Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.

• JMP has resulted in literally millions of dollars in ROI due to identification of correctable errors.
• Use of JMP control charts JMP has greatly simplified and improved interpretation of Lean, FMEA, and PDSA type analyses.
• Use of JMP has enable the testing and subsequent selection of 'best practices' saving uncounted hours in false starts based on 'collective experience'.
• The down side is that JMP is not a 'magic box', one still has to take care in applying the tools properly. Moreover, time-consuming approaches using JMP may still be the 'order of the day', because the service (even power user) is unaware of significant shortcuts available for free on the JMP community website.

Incentivized

• By embedding Logi in our solution and using the Logi Self-Service Module we can provide this flexibility to our users without requiring custom development work for each new request.
• We succeeded in developing embedded self-service analytics at scale with a combination of Logi analytics as front-end and a Cassandra data lake with Spark aggregation algorithms as back-end.
• We analyze the insurance industry and need to replicate different data formats across hundreds of databases to support multi-tenant (customer) BI reports and "ad hoc" data review on millions or hundreds of millions of records per customer.

Incentivized

• Easy to share and manage viewer access on a different level to help identify fraud.
• Faster report generation, increased revenue, better decision-making, and data storytelling.
• One-click access to business health and the ability to build/maintain more effective and efficient reports.
• It's easy to share and even manage access to viewers on a different level, and reports are done in a more visual and storytelling manner.

Incentivized