IBM Cognos Analytics vs. IBM SPSS Modeler

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
IBM SPSS Modeler
Score 7.8 out of 10
N/A
IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.
$499
per month
Pricing
IBM Cognos AnalyticsIBM SPSS Modeler
Editions & Modules
On Demand - Standard
$10.00
per month per user
On Demand - Premium
$40.00
per month per user
IBM SPSS Modeler Personal
4,670
per year
IBM SPSS Modeler Professional
7,000
per year
IBM SPSS Modeler Premium
11,600
per year
IBM SPSS Modeler Gold
contact IBM
per year
Offerings
Pricing Offerings
IBM Cognos AnalyticsIBM SPSS Modeler
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesYes
Entry-level Setup FeeOptionalOptional
Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.
More Pricing Information
Community Pulse
IBM Cognos AnalyticsIBM SPSS Modeler
Top Pros
Top Cons
Features
IBM Cognos AnalyticsIBM SPSS Modeler
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
IBM Cognos Analytics
7.9
102 Ratings
4% below category average
IBM SPSS Modeler
-
Ratings
Pixel Perfect reports8.593 Ratings00 Ratings
Customizable dashboards7.8100 Ratings00 Ratings
Report Formatting Templates7.497 Ratings00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
IBM Cognos Analytics
8.1
104 Ratings
0% below category average
IBM SPSS Modeler
-
Ratings
Drill-down analysis8.1102 Ratings00 Ratings
Formatting capabilities8.1103 Ratings00 Ratings
Integration with R or other statistical packages7.872 Ratings00 Ratings
Report sharing and collaboration8.4100 Ratings00 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
IBM Cognos Analytics
8.3
104 Ratings
1% below category average
IBM SPSS Modeler
-
Ratings
Publish to Web8.327 Ratings00 Ratings
Publish to PDF8.798 Ratings00 Ratings
Report Versioning8.626 Ratings00 Ratings
Report Delivery Scheduling8.0101 Ratings00 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
94 Ratings
0% above category average
IBM SPSS Modeler
-
Ratings
Pre-built visualization formats (heatmaps, scatter plots etc.)8.089 Ratings00 Ratings
Location Analytics / Geographic Visualization8.286 Ratings00 Ratings
Predictive Analytics8.182 Ratings00 Ratings
Pattern Recognition and Data Mining8.021 Ratings00 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
IBM Cognos Analytics
8.3
99 Ratings
4% below category average
IBM SPSS Modeler
-
Ratings
Multi-User Support (named login)8.496 Ratings00 Ratings
Role-Based Security Model8.395 Ratings00 Ratings
Multiple Access Permission Levels (Create, Read, Delete)8.295 Ratings00 Ratings
Report-Level Access Control8.424 Ratings00 Ratings
Single Sign-On (SSO)8.377 Ratings00 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
IBM Cognos Analytics
7.3
83 Ratings
8% below category average
IBM SPSS Modeler
-
Ratings
Responsive Design for Web Access7.977 Ratings00 Ratings
Mobile Application7.368 Ratings00 Ratings
Dashboard / Report / Visualization Interactivity on Mobile8.174 Ratings00 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
IBM Cognos Analytics
7.5
62 Ratings
5% below category average
IBM SPSS Modeler
-
Ratings
REST API7.359 Ratings00 Ratings
Javascript API7.658 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
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User Ratings
IBM Cognos AnalyticsIBM SPSS Modeler
Likelihood to Recommend
8.1
(127 ratings)
10.0
(6 ratings)
Likelihood to Renew
9.8
(27 ratings)
-
(0 ratings)
Usability
8.0
(8 ratings)
-
(0 ratings)
Availability
8.6
(4 ratings)
-
(0 ratings)
Performance
9.0
(5 ratings)
-
(0 ratings)
Support Rating
10.0
(8 ratings)
10.0
(1 ratings)
In-Person Training
8.7
(4 ratings)
-
(0 ratings)
Online Training
8.0
(4 ratings)
-
(0 ratings)
Implementation Rating
7.0
(7 ratings)
-
(0 ratings)
Configurability
8.0
(2 ratings)
-
(0 ratings)
Ease of integration
7.3
(3 ratings)
-
(0 ratings)
Product Scalability
8.3
(3 ratings)
-
(0 ratings)
Vendor post-sale
7.0
(1 ratings)
-
(0 ratings)
Vendor pre-sale
7.0
(1 ratings)
-
(0 ratings)
User Testimonials
IBM Cognos AnalyticsIBM SPSS Modeler
Likelihood to Recommend
IBM
Well suited: 1. We use the tool for data modeling as it helps in predictive data analysis for complex data, which is very much in line with real-life scenarios. 2. Options
of customizing & scheduling reports as per our
requirements basis. 3. Has a mobile application that works seamlessly. Less Appropriate: 1. API integration with minimal options is not up to the mark. Laptops get overheated when using the tool, from moderate to heavy use. 2. Also, there is a lag in the tool times. 3. There is a lot of scope to improve customer support & it's not up to industry standards. 4. Licensing
& Maintenance can go from cheap to expensive depending on the scope.
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IBM
Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
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Pros
IBM
  • It provides statistical analysis and predictive modeling which helps to forecast sales trends based on data and other factors.
  • It provides user friendly interface which helps users to explore data without extensive IT support. Like sales and marketing teams can use self service BI to analyze customer data and personalize campaigns for marketing.
  • It integrates well with IBM products and also with third party which enables organization to integrate with different products for better results and growth.
  • It provides security and governance features which maintains confidentiality, and compliance of data. It impose HIPAA compliance by providing role based access and encryption to protect sensitive data.
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IBM
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
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Cons
IBM
  • Uses a lot of the CPU of PC and can be only item running on computer sometimes
  • The error descriptions could be worded differently to help users find out what is exactly wrong with the report they are trying to write
  • Missing third party integration functionality that works succinctly
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IBM
  • Has very old style graphs, with lots of limitations.
  • Some advanced statistical functions cannot be done through the menu.
  • The data connectivity is not that extensive.
  • It's an expensive tool.
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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.
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IBM
No answers on this topic
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.
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IBM
No answers on this topic
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
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IBM
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.
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IBM
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.
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IBM
The online support board is helpful and the free add ons are incredibly appreciated.
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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
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
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IBM
No answers on this topic
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
No answers on this topic
Alternatives Considered
IBM
I like the cloud native character and ease of deployment with Sigma and ThogthSpot, I also like the metadata modelling capabilities of Power BI. I prefer the ability of Cognos to create and publish a metadata model that provides both ad hoc access and managed reporting and everything in between
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IBM
When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
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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.
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IBM
No answers on this topic
Return on Investment
IBM
  • I've rebuilt a few metadata models to make the associated reports run at around a fifth of the time.
  • I was able to write and sell an IBM Cognos Analytics with Watson extension pack to add additional functionality and to make report author's lives easier.
Read full review
IBM
  • Positive - Ease of decision making and reduction in product life cycle time.
  • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
  • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
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ScreenShots

IBM SPSS Modeler Screenshots

Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.