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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM Cognos Analytics

    Score7.7 out of 10
    N/AIBM Cognos is a full-featured business intelligence suite by IBM, designed for larger deployments. It comprises Query Studio, Reporting Studio, Analysis Studio and Event Studio, and Cognos Administration along with tools for Microsoft Office integration, full-text search, and dashboards.

    $11.25

    per month per user

    IBM SPSS Statistics

    Score8.1 out of 10
    N/ASPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).

    $105

    per month per user

    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

    Pricing
    IBM Cognos AnalyticsIBM SPSS StatisticsJMP
    Editions & Modules
    On Demand - Standard
    USD 11.25
    per month per user
    On Demand - Premium
    USD 44.90
    per month per user
    Base
    USD 3,830
    one-time fee per user
    Standard
    USD 8,440
    one-time fee per user
    Professional
    USD 16,900
    one-time fee per user
    Premium
    USD 25,200
    one-time fee per user
    Monthly subscription
    USD 105
    per month per user
    Annual subscription
    USD 1,188.00
    per year per user
    JMP
    $1320
    per year per user
    Offerings
    Pricing Offerings
    IBM Cognos AnalyticsIBM SPSS StatisticsJMP
    Free Trial
    YesYesYes
    Free/Freemium Version
    NoNoNo
    Premium Consulting/Integration Services
    YesNoNo
    Entry-level Setup FeeOptionalNo setup feeNo setup fee
    Additional Details——Bulk discounts available.
    More Pricing Information
    Community Pulse
    IBM Cognos AnalyticsIBM SPSS StatisticsJMP
    Considered Multiple Products
    IBM
    Chose IBM Cognos Analytics
    Tableau, Power BI, QlikView were the other options considered. Tableau lacked the following key components of business intelligence and analytics. Some other statistical functions that are available on the platform were not matched by Power BI. QlikView lacked robust …
    Incentivized
    Chose IBM Cognos Analytics
    MS BI: A lot of times we meet customers who are dealing with an MS BI maintenance nightmare and we try to ease their pain by implementing Cognos BI and their reporting and analysis system. Cognos BI is better than MS BI from ease of implementation to production support and …
    Incentivized
    IBM
    Chose IBM SPSS Statistics
    SAS is a very good product. SPSS provided our firm everythinbg we needed and was well within our budget. Also know that IBM is contunusely investing into SPSS. The roadmaps looks good.
    Incentivized
    Chose IBM SPSS Statistics
    IBM SPSS Statistics stacks up much better and overall gives the user a much better as well as simpler means to achieve their end goal. It provides a comprehensive set of well tested data management, along with statistical procedures in an easy to use and all in one package …
    Incentivized
    Chose IBM SPSS Statistics
    The price of IBM SPSS and its quality-price ratio was one of the triggers for choosing the software over the competition. The ease of obtaining a demo of the product and the continuous training it presents was another of the key points in the decision making we made in the …
    Incentivized
    Chose IBM SPSS Statistics
    Its better for quick tasks, Psychology, Sociology, may lack in complex models, AI, or business-decision-making models. It's better for things that you want to compare, correlate or detect influence of one on the other. It's worse that R for complex models, custom models, big …
    Incentivized
    Chose IBM SPSS Statistics
    None
    Incentivized
    Chose IBM SPSS Statistics
    Compared to other similar programs such as R or SAS I find that SPSS is more user friendly to the researcher. I also have noticed that SPSS is more commonly used in other companies and schools research studies. This is great because it can allow for a step by step replication …
    Incentivized
    Chose IBM SPSS Statistics
    I much prefer SPSS
    Incentivized
    Chose IBM SPSS Statistics
    I use Stata for tasks that SPSS cannot support, but ultimately SPSS has a short learning curve, strong statistical processing, and a mature tool set. SAS is also mature, but more programming based. JMP tries to 2nd guess what I need. NOTE: R (open source) is a great option …
    Incentivized
    Chose IBM SPSS Statistics
    If I didn't want to code, IBM SPSS would be after JMP and Tableau, and before SAS and R. The user interface is very clunky compared to the analytics software I stated. You could definitely learn to do basic analysis faster in SAS than SPSS. I selected SPSS to test the …
    Incentivized
    Chose IBM SPSS Statistics
    I have also used RStudio and SAS previously. In fact, I'm currently using RStudio since our SPSS license has expired. SPSS lacks the capabilities of these other two programs and it is far less intuitive. Larger data sets can be analyzed with R and SAS, but using these programs …
    Incentivized
    JMP Statistical Discovery
    Chose JMP
    We just needed to get the output that contains the statistical output, graphs but no programming.
    Incentivized
    Chose JMP
    Compared to other, similar programs, JMP is outstanding in ease of use and ability to be used by almost anyone across an organization. It is more fluid, user friendly, and, most importantly, requires no coding experience. The only two areas where it is not as good as …
    Incentivized
    Chose JMP
    For me, JMP is the best and easy way to run regressions. I wouldn't use it for other more advanced models. I decided to use it because we got it for free since we are technically an academic institution.
    Incentivized
    Chose JMP
    For what it does, it has better value and is easier to train other users to use.
    Incentivized
    Chose JMP
    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.
    Key User Insights
    Would buy again
    97%
    Would buy again
    93 Answers
    94%
    Would buy again
    49 Answers
    100%
    Would buy again
    9 Answers
    Delivers good value for the price
    94%
    Delivers good value for the price
    79 Answers
    91%
    Delivers good value for the price
    42 Answers
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    96%
    Happy with the feature set
    92 Answers
    98%
    Happy with the feature set
    51 Answers
    89%
    Happy with the feature set
    8 Answers
    Lived up to sales and marketing promises
    93%
    Lived up to sales and marketing promises
    55 Answers
    97%
    Lived up to sales and marketing promises
    34 Answers
    100%
    Lived up to sales and marketing promises
    6 Answers
    Implementation went as expected
    96%
    Implementation went as expected
    65 Answers
    97%
    Implementation went as expected
    35 Answers
    100%
    Implementation went as expected
    6 Answers
    Features
    IBM Cognos AnalyticsIBM SPSS StatisticsJMP
    BI Standard Reporting
    Comparison of BI Standard Reporting features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    7.7
    140 Ratings
    6% below category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    Pixel Perfect reports7.6131 Ratings00 Ratings00 Ratings
    Customizable dashboards8.0138 Ratings00 Ratings00 Ratings
    Report Formatting Templates7.5133 Ratings00 Ratings00 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    7.9
    140 Ratings
    1% below category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    Drill-down analysis7.4138 Ratings00 Ratings00 Ratings
    Formatting capabilities8.3141 Ratings00 Ratings00 Ratings
    Integration with R or other statistical packages7.398 Ratings00 Ratings00 Ratings
    Report sharing and collaboration8.6135 Ratings00 Ratings00 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    9.2
    138 Ratings
    11% above category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    Publish to Web9.838 Ratings00 Ratings00 Ratings
    Publish to PDF8.3134 Ratings00 Ratings00 Ratings
    Report Versioning9.835 Ratings00 Ratings00 Ratings
    Report Delivery Scheduling8.2136 Ratings00 Ratings00 Ratings
    Delivery to Remote Servers9.919 Ratings00 Ratings00 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    7.4
    126 Ratings
    8% below category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    Pre-built visualization formats (heatmaps, scatter plots etc.)7.9123 Ratings00 Ratings00 Ratings
    Location Analytics / Geographic Visualization8.0116 Ratings00 Ratings00 Ratings
    Predictive Analytics6.7112 Ratings00 Ratings00 Ratings
    Pattern Recognition and Data Mining6.949 Ratings00 Ratings00 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    7.8
    132 Ratings
    8% below category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    Multi-User Support (named login)7.5131 Ratings00 Ratings00 Ratings
    Role-Based Security Model7.5129 Ratings00 Ratings00 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)7.4129 Ratings00 Ratings00 Ratings
    Report-Level Access Control8.259 Ratings00 Ratings00 Ratings
    Single Sign-On (SSO)8.6113 Ratings00 Ratings00 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    6.3
    110 Ratings
    21% below category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    Responsive Design for Web Access6.7105 Ratings00 Ratings00 Ratings
    Mobile Application6.391 Ratings00 Ratings00 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile6.697 Ratings00 Ratings00 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of IBM Cognos Analytics and IBM SPSS Statistics and JMP
    Feature
    IBM Cognos Analytics
    9.2
    88 Ratings
    17% above category average
    IBM SPSS Statistics
    -
    Ratings
    JMP
    -
    Ratings
    REST API7.684 Ratings00 Ratings00 Ratings
    Javascript API7.780 Ratings00 Ratings00 Ratings
    iFrames9.913 Ratings00 Ratings00 Ratings
    Java API9.914 Ratings00 Ratings00 Ratings
    Themeable User Interface (UI)9.916 Ratings00 Ratings00 Ratings
    Customizable Platform (Open Source)9.910 Ratings00 Ratings00 Ratings
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    User Ratings
    IBM Cognos AnalyticsIBM SPSS StatisticsJMP
    Likelihood to Recommend
    8.0
    (160 ratings)
    8.5
    (116 ratings)
    9.8
    (30 ratings)
    Likelihood to Renew
    8.4
    (31 ratings)
    8.5
    (23 ratings)
    10.0
    (16 ratings)
    Usability
    7.3
    (10 ratings)
    8.0
    (15 ratings)
    8.8
    (7 ratings)
    Availability
    8.6
    (4 ratings)
    6.0
    (1 ratings)
    10.0
    (1 ratings)
    Performance
    9.0
    (5 ratings)
    6.0
    (1 ratings)
    10.0
    (1 ratings)
    Support Rating
    1.0
    (9 ratings)
    6.4
    (12 ratings)
    9.2
    (7 ratings)
    In-Person Training
    8.7
    (4 ratings)
    -
    (0 ratings)
    -
    (0 ratings)
    Online Training
    8.0
    (4 ratings)
    -
    (0 ratings)
    7.9
    (3 ratings)
    Implementation Rating
    7.0
    (7 ratings)
    8.7
    (7 ratings)
    9.6
    (2 ratings)
    Configurability
    7.0
    (3 ratings)
    5.0
    (1 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    8.6
    (40 ratings)
    -
    (0 ratings)
    4.0
    (1 ratings)
    Data Sources
    8.3
    (40 ratings)
    -
    (0 ratings)
    5.0
    (1 ratings)
    Ease of integration
    5.5
    (6 ratings)
    5.0
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    6.4
    (5 ratings)
    5.0
    (1 ratings)
    10.0
    (1 ratings)
    Vendor post-sale
    7.0
    (1 ratings)
    5.0
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    7.0
    (1 ratings)
    5.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM Cognos AnalyticsIBM SPSS StatisticsJMP
    Likelihood to Recommend
    IBM
    In our environment, we used to use a reporting tool called Crystal Reports and we replaced this tool with Cognos. I would recommend this switch for any one who's using a report tool that can be replaced with Cognos. This eliminates any JDBC or ODBC connections and User setups within any databases which was needed so the users can gain access to the report. Cognos makes logging in and fetching any report much easier.
    Incentivized
    Read full review
    IBM
    IBM SPSS Statistics is well suited for pretty much any data analytic scenario. It can handle extremely complex and large-scale datasets with ease. It especially shines if you have to do any kind of analyses that involve significance testing. Being able to do any number of significance tests (i.e., t-tests, chi-square, ANOVAs, etc.) right inside the tool is very valuable. The only scenario I would say it is less appropriate is if you need to work on a very small dataset and answer very simple questions, like frequencies or averages. In those cases, something like Excel could probably do the job just as easily.
    Incentivized
    Read full review
    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
    Read full review
    Pros
    IBM
    • Enterprise reporting - Create, customise, and run reports on sales trends, consumer sentiment, etc.
    • Dashboard creation and data exploration & analysis - Using drag and drop feature to create ad-hoc visualisation. Additionally, using AI powered natural language query feature for data analysis and dashboard input (formation of pie, bar, line charts). It's useful for no-technical person to put queries around the spreadsheet data to get quick answers.
    • Building insights for accurate decision making - Package reports with data backed insights for stakeholders in pdf, and Excel format to support business ad-hoc cases, forecasting and strategic recommendations on relevant asks.
    Incentivized
    Read full review
    IBM
    • SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
    • Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
    • SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
    • SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
    • In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
    Incentivized
    Read full review
    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.
    Read full review
    Cons
    IBM
    • IBM Cognos Analytics enables customer data segmentation, which is essential for marketing, improving and streamlining purchasing behavior and preferences. This helps companies create more targeted and effective marketing campaigns.
    • Our clients Through data analysis, we can identify and observe trends in the behavior of other clients, allowing us to anticipate needs and adjust strategies to avoid consequences.
    Incentivized
    Read full review
    IBM
    • Cost is becoming prohibitive.
    • Availability of procedures in the base package seems to be dwindling.
    • The copy-and-paste function from output to Excel is not as easy as it once was (now I have to do a "paste special").
    • Text and date handling are terrible.
    • Need to include AI-based NLP for survey verbatims and other text-based fields. This is becoming increasingly important in the CX world, yet SPSS seems to be ignoring it.
    Incentivized
    Read full review
    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.)
    Read full review
    Likelihood to Renew
    IBM
    For an existing solution, renewing licenses does provide a good return on investment. Additionally, while rolling out scorecards and dashboards with little adhoc capabilities, to end users, cognos is very easily scalable. It also allows to create a solution that has a mix of OLAP and relational data-sources, which is a limitation with other tools. Synchronizing with existing security setup is easy too.
    Read full review
    IBM
    Both
    money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis
    using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data
    entry and data analysis for my research. Output from SPSS is very easy to
    interpret for data analysis and findings
    Incentivized
    Read full review
    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.
    Read full review
    Usability
    IBM
    We have a strong user base (3500 users) that are highly utilizing this tool. Basic users are able to consume content within the applied security model. We have a set of advanced users that really push the limits of Cognos with Report and Query Studio. These users have created a lot of personal content and stored it in 'My Reports'. Users enjoy this flexibility.
    Read full review
    IBM
    Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.
    Incentivized
    Read full review
    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
    Read full review
    Reliability and Availability
    IBM
    Reports can typically be viewed through any browser that can access the server, so the availability is ultimately up to what the company utilizing it is comfortable with allowing, though report development tends to be more picky about browsers and settings as mentioned above. It also has an optional iPad app and general mobile browsing support, but dashboards lack the mobile compatibility. What keeps it from getting a higher score is the desktop tools that are vital to the development process. The compatibility with only Windows when the server has a wide range of compatibility can be a real sore point for a company that outfits its employees exclusively with Mac or Linux machines. Of course, if they are planning on outsourcing the development anyways, it's a rather moot point
    Read full review
    IBM
    SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data
    Incentivized
    Read full review
    JMP Statistical Discovery
    No answers on this topic
    Performance
    IBM
    Overall no major complaints but it doesn't handle DMR (Dimensionally Modeled for Relational) very well. DMR modelling is a capability that IBM Cognos Framework Manager provides allowing you to specify dimensional information for relational metadata and allows for OLAP-style queries. However, the capability is not very efficient and, for example, if I'm using only 2 columns on a 20-column model, the software is not smart enough to exclude 18 columns and the query side gets progressively larger and larger until it's effectively unusable.
    Read full review
    IBM
    SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.
    Incentivized
    Read full review
    JMP Statistical Discovery
    No answers on this topic
    Support Rating
    IBM
    Why is their web application not working as fast as you think it should? They never know, and it is always a a bunch of shots in the dark to find out. Trying to download software from them is like trying to find a book at the library before computers were invented.
    Incentivized
    Read full review
    IBM
    I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
    Read full review
    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
    Read full review
    In-Person Training
    IBM
    Onsite training provided by IBM Cognos was effective and as expected. They did not perform training with our data which was a bit difficult for our end-users.
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    IBM
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    JMP Statistical Discovery
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    Online Training
    IBM
    The online courses they offer are thorough and presented in such a way that someone who isn't already familiar with the general design methodologies used in this field will be capable of making a good design. The training environments are provided as a fully self contained virtual machine with everything needed already to create the environments. We've had some persisting issues with the environments becoming unavailable, but support has been responsive when these issues arise and straightening them out for us
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    IBM
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    JMP Statistical Discovery
    I have not used your online training. I use JMP manuals and SAS direct help.
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    Implementation Rating
    IBM
    Make sure that any custom tables that you have, are built into your metadata packages. You can still access them via SQL queries in Cognos, but it is much easier to have them as a part of the available metadata packages.
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    IBM
    Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
    Incentivized
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    JMP Statistical Discovery
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    Alternatives Considered
    IBM
    Power BI is stronger for quick ad-hoc analysis and dashboards, but IBM Cognos Analytics is better when consistency, precision, and mass distribution matter. Tableau is best for interactive analysis, while IBM Cognos Analytics is better for standardized, repeatable enterprise reporting. Sigma shines for customizable dashboards and drill-down analysis while IBM Cognos Analytics holds an edge in data discovery and visualization.
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    IBM
    If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 years ago and has shown no desire to improve.
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    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.
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    Scalability
    IBM
    We rate IBM Cognos Analytics a 9 out of 10 for overall scalability. The platform handles large numbers of users, reports, and analytical workloads very reliably. We have experienced strong performance even in demanding enterprise environments with substantial data volumes. Its architecture provides sufficient flexibility to scale resources according to demand, making it well suited for large, business-critical deployments.
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    IBM
    I am neutral because I have not had to look into scalability since I am using as a student.
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    JMP Statistical Discovery
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    Return on Investment
    IBM
    • The platform can be pretty pricey.
    • Convoluted contracts and they fine you for any breach during audits.
    • Things are changed between releases without any warning and break.
    • It is second to none at being able to customize list and crosstab type reports.
    • You can easily set up a report to be emailed out every day and even have it export the report to a shared folder.
    • On-prem environments can be scaled up pretty much as much as you would like.
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    IBM
    • I found SPSS easier to use than SAS as it's more intuitive to me.
    • The learning curve to use SPSS is less compared to SAS.
    • I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.
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    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).
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    ScreenShots

    IBM Cognos Analytics Screenshots

    Product screenshotProduct screenshotProduct screenshotProduct screenshotProduct screenshotProduct screenshot

    IBM SPSS Statistics Screenshots

    Screenshot of SPSS Statistics Forecasting. This enables users to build time-series forecasts regardless of their skill level.Screenshot of SPSS Statistics Regression. These predict categorical outcomes and apply nonlinear regression procedures.Screenshot of IBM SPSS Statistics Neural Networks. These can discover complex relationships and improve predictive models.Screenshot of IBM SPSS Statistics Curated Help. These can interpret correlation output.Screenshot of IBM SPSS Statistics AI Output Assistant interprets statistical output in easy to consume language

    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.