IBM Cognos Analytics vs. JMP Statistical Discovery Software from SAS

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Cognos Analytics
Score 8.2 out of 10
N/A
IBM 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.
$10
per month per user
JMP Statistical Discovery Software from SAS
Score 8.5 out of 10
N/A
JMP is a division of SAS and the JMP family of products provide statistical discovery tools linked to dynamic data visualizations.
$125
per month
Pricing
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
Editions & Modules
On Demand - Standard
$10.00
per month per user
On Demand - Premium
$40.00
per month per user
Personal License
$125.00
per month
Corporate License
$1,510.00
Per Month Per Unit
Offerings
Pricing Offerings
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
Top Pros
Top Cons
Features
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
IBM Cognos Analytics
7.9
101 Ratings
3% below category average
JMP Statistical Discovery Software from SAS
9.5
9 Ratings
12% above category average
Pixel Perfect reports8.592 Ratings10.01 Ratings
Customizable dashboards7.799 Ratings9.09 Ratings
Report Formatting Templates7.496 Ratings00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
IBM Cognos Analytics
8.1
103 Ratings
0% above category average
JMP Statistical Discovery Software from SAS
7.6
13 Ratings
5% below category average
Drill-down analysis8.0101 Ratings7.813 Ratings
Formatting capabilities8.1102 Ratings6.612 Ratings
Integration with R or other statistical packages7.871 Ratings7.810 Ratings
Report sharing and collaboration8.499 Ratings8.213 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
IBM Cognos Analytics
8.3
103 Ratings
0% below category average
JMP Statistical Discovery Software from SAS
8.7
12 Ratings
4% above category average
Publish to Web8.327 Ratings9.09 Ratings
Publish to PDF8.697 Ratings8.712 Ratings
Report Versioning8.626 Ratings7.01 Ratings
Report Delivery Scheduling7.9100 Ratings10.01 Ratings
Delivery to Remote Servers8.112 Ratings00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
IBM Cognos Analytics
8.1
93 Ratings
1% above category average
JMP Statistical Discovery Software from SAS
8.3
16 Ratings
1% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)8.188 Ratings8.016 Ratings
Location Analytics / Geographic Visualization8.285 Ratings9.013 Ratings
Predictive Analytics8.281 Ratings7.913 Ratings
Pattern Recognition and Data Mining8.020 Ratings00 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
IBM Cognos Analytics
8.3
98 Ratings
3% below category average
JMP Statistical Discovery Software from SAS
-
Ratings
Multi-User Support (named login)8.395 Ratings00 Ratings
Role-Based Security Model8.394 Ratings00 Ratings
Multiple Access Permission Levels (Create, Read, Delete)8.294 Ratings00 Ratings
Report-Level Access Control8.423 Ratings00 Ratings
Single Sign-On (SSO)8.376 Ratings00 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
IBM Cognos Analytics
7.3
81 Ratings
9% below category average
JMP Statistical Discovery Software from SAS
-
Ratings
Responsive Design for Web Access7.975 Ratings00 Ratings
Mobile Application7.366 Ratings00 Ratings
Dashboard / Report / Visualization Interactivity on Mobile8.272 Ratings00 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
IBM Cognos Analytics
7.4
60 Ratings
6% below category average
JMP Statistical Discovery Software from SAS
-
Ratings
REST API7.257 Ratings00 Ratings
Javascript API7.556 Ratings00 Ratings
iFrames8.39 Ratings00 Ratings
Java API6.911 Ratings00 Ratings
Themeable User Interface (UI)7.110 Ratings00 Ratings
Customizable Platform (Open Source)7.87 Ratings00 Ratings
Best Alternatives
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
Small Businesses
SAP Crystal
SAP Crystal
Score 8.9 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Reveal
Reveal
Score 9.9 out of 10
Mathematica
Mathematica
Score 8.2 out of 10
Enterprises
Jaspersoft Community Edition
Jaspersoft Community Edition
Score 9.7 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
Likelihood to Recommend
8.1
(126 ratings)
7.4
(28 ratings)
Likelihood to Renew
9.6
(27 ratings)
10.0
(16 ratings)
Usability
8.0
(8 ratings)
10.0
(5 ratings)
Availability
8.6
(4 ratings)
10.0
(1 ratings)
Performance
9.0
(5 ratings)
10.0
(1 ratings)
Support Rating
10.0
(8 ratings)
9.2
(7 ratings)
In-Person Training
8.7
(4 ratings)
-
(0 ratings)
Online Training
8.0
(4 ratings)
7.9
(3 ratings)
Implementation Rating
7.0
(7 ratings)
9.6
(2 ratings)
Configurability
8.0
(2 ratings)
-
(0 ratings)
Ease of integration
7.3
(3 ratings)
-
(0 ratings)
Product Scalability
8.3
(3 ratings)
10.0
(1 ratings)
Vendor post-sale
7.0
(1 ratings)
-
(0 ratings)
Vendor pre-sale
7.0
(1 ratings)
-
(0 ratings)
User Testimonials
IBM Cognos AnalyticsJMP Statistical Discovery Software from SAS
Likelihood to Recommend
IBM
Our first and most basic scenario was to automatize the creation and publication/sharing of business reports that used to be created manually by employees throughout our organization. Using Cognos for that first use case worked well. The advanced analytics functionalities we used on the aggregated data were also as expected. However, the user interface is not always intuitive, and there is a steep learning curve, so I would recommend Cognos only to large organizations where there is a need for the most advanced functionalities (AI analysis/prediction).
Read full review
SAS
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
  • We use the tool for data modeling as it helps in predictive data analysis for complex data, which is very similar to real-life scenarios.
  • Options of customizing & scheduling reports as per our requirements basis.
  • Has mobile application which works seamless.
Read full review
SAS
  • 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
  • Sometimes there might be performance issues when dealing with large and complex data.
  • Although IBM provides full documentation but sometimes it's difficult to find answers to questions and connect with their customer support.
  • It relies on external tools for data cleaning, transformation and also for some integration tasks. It can also improve on providing wider range of data sources for integration.
Read full review
SAS
  • 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
SAS
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
SAS
The overall usability of JMP is extremely good. What I really love about it is its ability to be useable for novices who have no coding experience, which is not the case with most other, similar, programs. It can output a fast and easy analysis without too much prior coding or statistical knowledge.
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
SAS
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
SAS
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.
Read full review
SAS
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.
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.
Read full review
SAS
No answers on this topic
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
Read full review
SAS
I have not used your online training. I use JMP manuals and SAS direct help.
Read full review
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.
Read full review
SAS
No answers on this topic
Alternatives Considered
IBM
In the past Management had used Excel and Workiva capabilities to create the reporting dashboards that were being used to make decisions. Since switching to IBM Cognos Analytics the Company has been much more efficient and decision making has been streamlined. IBM Cognos Analytics was chosen due to its reputation and data visualization capabilities and neither have been wrong.
Read full review
SAS
It is great because it has UI menus but it costs money whereas the other programs are free. That makes it ideal for beginners but I think that RStudio and Python are going to make someone a lot more marketable for future opportunities since most companies won't pay for the software when there is a great free option.
Read full review
Scalability
IBM
The Cognos architecture is well suited for scalability. However, the architecture must be designed with scalability in mind from day one of the implementation. We recently upgraded from 10.1 to 10.2.1 and took the opportunity to revamp our architecture. It is now poised for future growth and scalability.
Read full review
SAS
No answers on this topic
Return on Investment
IBM
  • High ROI with well designed solutions. Supported by scalable deployment, robust security model and ability to create valuable content.
  • High ROI where well designed data models can be deployed with a common metadata layer to a variety of users and use cases.
  • High ROI in an environment that includes a variety of vendors and best of breed products within the overall platform
Read full review
SAS
  • 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).
Read full review
ScreenShots

JMP Statistical Discovery Software from SAS Screenshots

Screenshot of Graph Builder.Screenshot of Design of ExperimentsScreenshot of Hierarchical and KMeans clustering are available from the Multivariate platform.Screenshot of Scatterplot Multivariate AnalysisScreenshot of Survey Analysis