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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    JMP

    Score9.8 out of 10
    N/AJMP® is statistical analysis software with capabilities that span from data access to advanced statistical techniques, with click of a button sharing. The software is interactive and visual, and statistically deep enough to allow users to see and explore data.

    $1,320

    per year per user

    TIBCO Data Virtualization

    Score8.6 out of 10
    N/ATIBCO Data Virtualization is an enterprise data virtualization solution that orchestrates access to multiple and varied data sources and delivers the datasets and IT-curated data services foundation for nearly any solution.N/A
    Pricing
    JMPTIBCO Data Virtualization
    Editions & Modules
    JMP
    $1320
    per year per user
    No answers on this topic
    Offerings
    Pricing Offerings
    JMPTIBCO Data Virtualization
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional DetailsBulk discounts available.—
    More Pricing Information
    Community Pulse
    JMPTIBCO Data Virtualization
    Considered Both Products
    JMP Statistical Discovery
    No answer on this topic
    Cloud Software Group
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    9 Answers
    78%
    Would buy again
    28 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    9 Answers
    97%
    Delivers good value for the price
    28 Answers
    Happy with the feature set
    89%
    Happy with the feature set
    8 Answers
    89%
    Happy with the feature set
    31 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    6 Answers
    100%
    Lived up to sales and marketing promises
    24 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    6 Answers
    87%
    Implementation went as expected
    26 Answers
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    JMPTIBCO Data Virtualization
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    Score9 out of 10
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    Alteryx Platform
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    All AlternativesView all alternativesView all alternatives
    User Ratings
    JMPTIBCO Data Virtualization
    Likelihood to Recommend
    9.8
    (30 ratings)
    7.1
    (43 ratings)
    Likelihood to Renew
    10.0
    (16 ratings)
    6.1
    (3 ratings)
    Usability
    8.8
    (7 ratings)
    5.4
    (5 ratings)
    Availability
    10.0
    (1 ratings)
    8.0
    (2 ratings)
    Performance
    10.0
    (1 ratings)
    6.6
    (20 ratings)
    Support Rating
    9.2
    (7 ratings)
    7.9
    (21 ratings)
    Online Training
    7.9
    (3 ratings)
    8.0
    (1 ratings)
    Implementation Rating
    9.6
    (2 ratings)
    7.9
    (3 ratings)
    Configurability
    -
    (0 ratings)
    8.0
    (1 ratings)
    Data Sharing and Collaboration
    4.0
    (1 ratings)
    -
    (0 ratings)
    Data Sources
    5.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    -
    (0 ratings)
    3.0
    (1 ratings)
    Product Scalability
    10.0
    (1 ratings)
    8.0
    (2 ratings)
    Vendor post-sale
    -
    (0 ratings)
    8.0
    (1 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    8.0
    (1 ratings)
    User Testimonials
    JMPTIBCO Data Virtualization
    Likelihood to Recommend
    JMP Statistical Discovery
    It is perfectly suited for statistical analyses, but I would not recommend JMP for users who do not have a statistical background. As previously stated, the learning curve is exceptionally steep, and I think that it would prove to be too steep for those without statistical background/knowledge
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    Cloud Software Group
    TIBCO Data Virtualization is well suited for customers who are challenged to deal with extracting data from dozens of different sources and systems, and do not have the time and liberty to hire data engineers and/or ETL developers to write dozens or hundreds of complex ETLs. However, there are situations where TIBCO Data Virtualization severely underperforms, and those are where we are dealing with large volumes of data, in tera bytes or peta byte scale system. For example, a messaging queue which sends 200 million messages every hour will choke TIBCO Data Virtualization if the technology is chosen to route the data.
    Incentivized
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    Pros
    JMP Statistical Discovery
    • JMP is designed from the ground-up to be a tool for analysts who do not have PhDs in Statistics without in anyway "dumbing down" the level of statistical analysis applied. In fact, JMP operationalizes the most advanced statistical methods. JMP's design is centred on the JMP data table and dialog boxes. It is data focused not jargon-focussed. So, unlike other software where you must choose the correct statistical method (eg. contingency, ANOVA, linear regression, etc.), with JMP you simply assign the columns in a dialog into roles in the analysis and it chooses the correct statistical method. It's a small thing but it reflects the thinking of the developers: analysts know their data and should only have to think about their data. Analyses should flow from there.
    • JMP makes most things interactive and visual. This makes analyses dynamic and engaging and obviates the complete dependence on understanding p-values and other statistical concepts(though they are all there) that are often found to be foreign or intimidating.
    • One of the best examples of this is JMP's profiler. Rather than looking at static figures in a spreadsheet, or a series of formulas, JMP profiles the formulas interactively. You can monitor the effect of changing factors (Xs) and see how they interact with other factors and the responses. You can also specify desirability (maximize, maximize, match-target) and their relative importances to find factor settings that are optimal. I have spent many lengthy meetings working with the profiler to review design and process options with never a dull moment.
    • The design of experiments (DOE) platform is simply outstanding and, in fact, the principal developers of it have won several awards. Over the last 15 years, using methods broadly known as an "exchange algorithm," JMP can create designs that are far more flexible than conventional designs. This means, for example, that you can create a design with just the interactions that are of interest; you can selectively choose those interactions that are not of interest and drop collecting their associated combinations.
    • Classical designs are rigid. For example, a Box-Benhken or other response surface design can have only continuous factors. What if you want to investigate these continuous factors along with other categorical factors such as different categorical variables such as materials or different furnace designs and look at the interaction among all factors? This common scenario cannot be handled with conventional designs but are easily accommodated with JMP's Custom DOE platform.
    • The whole point of DOE is to be able to look at multiple effects comprehensively but determine each one's influence in near or complete isolation. The custom design platform, because it produces uniques designs, provides the means to evaluate just how isolated the effects are. This can be done before collecting data because this important property of the DOE is a function of the design, not the data. By evaluating these graphical reports of the quality of the design, the analyst can make adjustments, adding or reducing runs, to optimize cost, effort and expected learnings.
    • Over the last number of releases of JMP, which appear about every 18 months now, they have skipped the dialog boxes to direct, drag-and-drop analyses for building graphs and tables as well as Statistical Process Control Charts. Interactivity such as this allows analysts to "be in the moment." As with all aspects of JMP, they are thinking of their subject matter without the cumbersomeness associated with having to think about statistical methods. It's rather like a CEO thinking about growing the business without having to think about every nuance and intricacy of accounting. The statistical thinking is burned into the design of JMP.
    • Without data analysis is not possible. Getting data into a situation where it can be analyzed can be a major hassle. JMP can pull data from a variety of sources including Excel spreadsheets, CSV, direct data feeds and databases via ODBC. Once the data is in JMP it has all the expected data manipulation capabilities to form it for analysis.
    • Back in 2000 JMP added a scripting language (JMP Scripting Language or JSL for short) to JMP. With JSL you can automate routine analyses without any coding, you can add specific analyses that JMP does not do out of the box and you can create entire analytical systems and workflows. We have done all three. For example, one consumer products company we are working with now has a need for a variant of a popular non-parametric analysis that they have employed for years. This method will be found in one of the menus and appear as if it were part of JMP to begin with. As for large systems, we have written some that are tens of thousands of lines that take the form of virtual labs and process control systems among others.
    • JSL applications can be bundled and distributed as JMP Add-ins which make it really easy for users to add to their JMP installation. All they need to do is double-click on the add-in file and it's installed. Pharmaceutical companies and others who are regulated or simply want to control the JMP environment can lock-down JMP's installation and prevent users from adding or changing functionality. Here, add-ins can be distributed from a central location that is authorized and protected to users world-wide.
    • JMP's technical support is second to none. They take questions by phone and email. I usually send email knowing that I'll get an informed response within 24 hours and if they cannot resolve a problem they proactively keep you informed about what is being done to resolve the issue or answer your question.
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    Cloud Software Group
    • Connecting to different data silos and presenting the data as a singled unified layer of data.
    • Exposing data to Technical and non technical users through Web UI or reporting tools
    • Secured exposure of data as web services.
    • Row level and column level data security
    • Multi tenancy data security.
    • Real time data by connecting to the operational databases
    • Historical data generation
    Incentivized
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    Cons
    JMP Statistical Discovery
    • In general JMP is much better fit for a general "data mining" type application. If you want a specific statistics based toolbox, (meaning you just want to run some predetermined test, like testing for a different proportion) then JMP works, but is not the best. JMP is much more suited to taking a data set and starting from "square 1" and exploring it through a range of analytics.
    • The CPK (process capability) module output is shockingly poor in JMP. This sticks out because, while as a rule everything in JMP is very visual and presentable, the CPK graph is a single-line-on-grey-background drawing. It is not intuitive, and really doesn't tell the story. (This is in contrast with a capability graph in Minitab, which is intuitive and tells a story right off.) This is also the case with the "guage study" output, used for mulivary analysis in a Six Sigma project. It is not intuitive and you need to do a lot of tweaking to make the graph tell you the story right off. I have given this feedback to JMP, and it is possible that it will be addressed in future versions.
    • I've never heard of JMP allowing floating licenses in a company. This will ALWAYS be a huge sticking point for small to middle size companies, that don't have teams people dedicated to analytics all day. If every person that would do problem solving needs his/her own seat, the cost can be prohibitive. (It gets cheaper by the seat as you add licenses, but for a small company that might get no more than 5 users, it is still a hard sell.)
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    Cloud Software Group
    • Performance of TDV Studio (its own IDE) is poor.
    • Performance of TDV repository database is rather poor for larger numbers of objects .(Note: We have approx. 9tsd objects introspected in TDV and approx. 20tsd objects generated in upper DV layers.)
    • Propagation of privileges to parent/child dependencies does not work when applying recursively on a folder. (It's a huge setback when working with large number of objects organized semantically into subfolders.)
    • Lack of command line client interface for scripting at the time of version 8.4 (I had to write my own CLI.)
    • TDV Studio does an absolutely horrible job with its own code editors when indentation is in place. Also, the editor is brutally slow and feature-poor.
    • Tracking privileges on the level of table/view columns causes occasional problems when regranting.
    • TDV's stored programs ("SQL scripts" in their own terminology) compiler leaves out many syntactic and semantic checks, making them hugely prone to run-time errors.
    • TDV Server's REST API is a very poor (in terms of features) and flawed cousin to its SOAP API (at the time of version 8.4).
    Incentivized
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    Likelihood to Renew
    JMP Statistical Discovery
    JMP has been good at releasing updates and adding new features and their support is good. Analytics is quick and you don't need scripting/programming experience. It has been used organization wide, and works well in that respect. Open source means that there are concerns regarding timely support. Cheap licensing and easy to maintain.
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    Cloud Software Group
    It is useful for us to see the data and do analysis. Also we use it to generate reports and see trends or gather insights
    Incentivized
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    Usability
    JMP Statistical Discovery
    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
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    Cloud Software Group
    TDV's interface is a bit dated and not entirely intuitive. Would recommend some UX design review as the interface leaves a bit to be better understood to be used by users without inherent knowledge of Tibco. Overall I'd suggest more improvement here to ensure usability by a lesser tech audience.
    Incentivized
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    Reliability and Availability
    JMP Statistical Discovery
    No answers on this topic
    Cloud Software Group
    We have never encountered issues where it was unavailable when we needed it.
    Incentivized
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    Performance
    JMP Statistical Discovery
    No answers on this topic
    Cloud Software Group
    This product's performance is very consistent. It is extremely rare for templates to fail. I've been using this software for 5 years and find it to be both simple and powerful. The impact within the company has been very positive as different processes in different areas, such as data analysis, development, and integrations, have been improved, and, best of all, it has not affected the users. Various systems with which it is connected in order to obtain information.
    Incentivized
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    Support Rating
    JMP Statistical Discovery
    Support is great and give ease of contact, rapid response, and willingness to 'stick to the task' until resolution or acknowledgement that the problem would have to be resolved in a future build. Basically, one gets the very real sense that another human being is sensitive to your problems - great or small.
    Incentivized
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    Cloud Software Group
    On a few occasions I have asked TIBCO technical support for help because I have adapted perfectly to their tools, but in those few that I have communicated with their technical team I have received personalized, attentive, responsible attention and I am always assisted by an expert staff the topic. A TIBCO technical support technician spent more than an hour helping me to solve a problem in the initial stage of implementation in my department and this is something that I always appreciate.
    Incentivized
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    Online Training
    JMP Statistical Discovery
    I have not used your online training. I use JMP manuals and SAS direct help.
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    Cloud Software Group
    The training was helpful. I was able to understand how to use TIBCO for the data load process that we implemented and how to perform various troubleshooting steps based on the training I received. The technician was thorough and took the time to answer any questions. Once we were shown how to use TIBCO in the test environment, we were able to configure the production environment ourselves.
    Incentivized
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    Implementation Rating
    JMP Statistical Discovery
    No answers on this topic
    Cloud Software Group
    Other vendors have clearer, more visual implementation documentation. We also did not have our data architect and and server administrator available full-time for implementation. In the future, we will secure the necessary internal resources.
    Incentivized
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    Alternatives Considered
    JMP Statistical Discovery
    MS Excel with AnalysisToolPak provides a home-grown solution, but requires a high degree of upkeep and is difficult to hand off. Minitab is the closes competitor, but JMP is better suited to the production environment, roughly equivalent in price, and has superior support.
    Incentivized
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    Cloud Software Group
    We did not need to evaluate another technology in the same category for data virtualization, since we are 100% sure of the capabilities and benefits that we would have with TIBCO Data Virtualization, both for market positioning as well as success stories from other companies. great renown worldwide. From the first day of use, it meets our needs to provide the expected solutions.
    Incentivized
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    Scalability
    JMP Statistical Discovery
    No answers on this topic
    Cloud Software Group
    Good scaling
    Incentivized
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    Return on Investment
    JMP Statistical Discovery
    • ROI: Even if the cost can be high, the insights you get out of the tool would definitely be much more valuable than the actual cost of the software. In my case, most of the results of your analysis were shown to the client, who was blown away, making the money spent well worth for us.
    • Potential negative: If you are not sure your team will use it, there's a chance you will just waste money. Sometimes the IT department (usually) tries to deploy a better tool for the entire organization but they keep using the old tool they are used too (most likely MS Excel).
    Incentivized
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    Cloud Software Group
    • We took spreadsheets that took hours a month to update and made them update automatically using TDV, saving hours a month of analyst time
    • The incremental cost of TDV relative to straight spotfire licensing made it a no-brainer due to the ease of data management
    • We continue to automate legacy business processes in TDV, saving time all over the organization.
    Incentivized
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    ScreenShots

    JMP Screenshots

    Screenshot of in JMP, how all graphical displays and the data table are linked.Screenshot of a few designed experiments, for more understanding and maximum impact. Users can understand cause and effect using statistically designed experiments — even with limited resources.Screenshot of an example of Predictive Modeling in JMP Pro's Prediction Profiler, used to build better models for more confident decision making.Screenshot of example outputs, built with tools designed for quality and reliability.

    TIBCO Data Virtualization Screenshots

    Screenshot of Data Flow EditorScreenshot of Data CatalogScreenshot of Transform Editor