IBM SPSS Modeler Reviews

Vendor: IBM

4.0 out of 5

39 reviews
86% willing to recommend

2,126 followers

What is IBM SPSS Modeler?

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

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IBM SPSS Modeler is the #4 ranked solution in top Data Mining solutions and #13 ranked solution in top Data Science Platforms. PeerSpot users give IBM SPSS Modeler an average rating of 8.0 out of 10. Based on the analysis of the 39 most recent IBM SPSS Modeler reviews, the overall sentiment is positive, with a sentiment score of 6.6. (Among the highest in the category). IBM SPSS Modeler is most commonly compared to KNIME: IBM SPSS Modeler vs KNIME. IBM SPSS Modeler is popular among the large enterprise segment, accounting for 64% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 13% of all views.

Helped 824,067 peers since 2012

Featured reviews

PeterHuo

Application Architect at Canada Border Services Agency

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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EzzAbdelfattah

Associate Professor of Statistics at KAU

The time series should be improved. The time series is a very important issue, however, it is not given its value in the package as it should be. They have only maybe one or two nodes. It needs more than that. Also, it needs to be easier to use, for instance, you have, for the regression techniques, an assembled way for the automation that the model can detect the type of the logistic regression. If it is binary or multinomial or whatever. For the time field, they have an expert model, however, it is not as strong as regression techniques. Therefore, they need to work more on the time series. Right now, with the Modeler, using unstructured data means needing to pay attention to IBM Modeler, including how to deal with the pictures. Currently the data, in the beginning, was structured, like an organized spreadsheet, however, now, you have to use unstructured data like pictures, voice, even location maps. This area needs improvement. If they can add this to the Modeler, it would be number one around the world.

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Levi Dovillaire

Senior Paper Technology Manager, EMEA at Valmet

I work with many data and tags. The product does not have a search function for tags. I cannot search for the name of the tag. I need to go through a list to find it. The software is old. The solution must be updated. It should also be a little bit faster. If we change the name of a field, the change should reflect in all the nodes we use later.

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IBM SPSS Modeler mindshare

Product category:

As of December 2024, the mindshare of IBM SPSS Modeler in the Data Mining category stands at 17.2%, up from 16.6% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Data Mining

PeerAnalyst reports

Type	Title	Date
Category	Data Mining	Dec 22, 2024	Download
Product	Reviews, tips, and advice from real users	Dec 22, 2024	Download
Comparison	IBM SPSS Modeler vs KNIME	Dec 22, 2024	Download
Comparison	IBM SPSS Modeler vs Weka	Dec 22, 2024	Download
Comparison	IBM SPSS Modeler vs IBM SPSS Statistics	Dec 22, 2024	Download

Title	Rating	Mindshare	Recommending
KNIME	4.0	26.1%	94%	59 interviews Add to research
IBM SPSS Statistics	4.0	15.1%	91%	37 interviews Add to research

Valuable Features

IBM SPSS Modeler is highly valued for its ease of use and visual programming without coding, robust statistical tools, integration with Python and R, and automation features like data cleansing and feature engineering. Users appreciate the drag-and-drop interface, powerful machine learning algorithms, data handling capabilities, and clear algorithm identification. The platform's ability to handle large datasets, quick data preparation, and customization options are also highlighted as significant advantages.

"I was familiar with using IBM SPSS Modeler separately in the private sector before that. It's a good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data."
"Compared to other tools, the product works much easier to analyze data without coding."
"We have full control of the data handling process."

Room for Improvement

IBM SPSS Modeler users find it expensive and desire better integration with tools like Tableau and Power BI. The addition of more advanced machine learning algorithms and customization options is requested. Users want improved time series capabilities, more visualizations, and faster performance. The platform's reliance on Windows, lack of support for open-source languages, and weak documentation are concerns. Enhancements in formula writing and automation processes are also needed, alongside better marketing and user interface flexibility.

"There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database."
"The platform's cloud version needs improvements."
"The product does not have a search function for tags."

ROI

Pricing

IBM SPSS Modeler is positioned competitively within Gartner's top quadrant, with pricing adjustable based on organizational plans. Licensing is flexible, typically costing around $5,000 to $9,000 annually. Discounts, up to 70%, are available at quarter-end. Education-related users may access free versions. While potentially expensive, bundle discounts are possible for IBM product users. Additional costs can arise from required features and Linux deployment. Pricing satisfaction varies, often rated between five and seven out of ten.

"The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten users use the server with ten licenses, it runs faster. But if forty users use the same appliance, everything slows down. People then think it's not easy to do things and prefer using remote tools like Python to extract data from the database. It's not about being expensive or cheap, but about people's knowledge and experience in how to do the work."
"It is an expensive product."
"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

Popular Use Cases

Organizations primarily use IBM SPSS Modeler for analytics, predictive modeling, and data exploration. They leverage its capabilities for customer segmentation, churn analysis, and quick prototyping. With integration options for R and Python, users conduct advanced analytics and machine learning tasks. IBM SPSS Modeler facilitates data preparation, modeling, and real-time data manipulation. It is also employed in educational settings for teaching data science and running analyses on diverse datasets, including economic impact and business analytics.

Service and Support

IBM SPSS Modeler support exhibits mixed experiences. Some find value in technical assistance and online documentation, while others report difficulty in contact and receiving satisfactory help. Local support varies, with some relying on IBM partners. Installation and response times may be slow, and documentation requires improvement. Experiences with technical support range from satisfactory to needing enhancement, with accents noted as a barrier. Some users manage without requiring external technical help.

Deployment

Users generally find IBM SPSS Modeler's initial setup straightforward, though some experience complexity, especially with server setups. Many appreciate guidance provided during installation. Issues often arise due to organizational environments rather than the tool itself. Upgrades are usually simple, but involve considerations of multiple components. Time involvement varies, with fast deployments reported. Practice and familiarity help mitigate data issues. Some users require additional components for workflow sharing and automation.

Scalability

IBM SPSS Modeler is generally considered scalable by many users. Some highlight its ease of scaling and integration, especially for large enterprises, while others find it financially restrictive or technically limiting, particularly for smaller organizations. A few users mention dependency on hardware constraints and note financial and technical considerations when managing scalability. Feedback varies, with some rating it highly, while others see room for improvement.

Stability

IBM SPSS Modeler is generally stable, with most users finding it reliable. Some experience occasional crashes, especially with intensive tasks or specific settings. Issues such as canvas bugs, encoding problems, and regional setting conflicts have been noted. Users appreciate the maturity of the software; it performs well when background configurations are finalized. New versions improve functionality, yet concerns about specific workflows and outages remain for some. Stability ratings vary, commonly between seven and nine out of ten.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our IBM SPSS Modeler Buyer's Guide for additional reliable information.

Review data by company size

By reviewers

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Top industries

By visitors reading reviews

Educational Organization

13%

Financial Services Firm

13%

Computer Software Company

University

Government

Manufacturing Company

Healthcare Company

Construction Company

Retailer

Insurance Company

Energy/Utilities Company

Real Estate/Law Firm

Non Profit

Media Company

Comms Service Provider

Wholesaler/Distributor

Mining And Metals Company

Transportation Company

Hospitality Company

Performing Arts

Outsourcing Company

Legal Firm

Recreational Facilities/Services Company

Engineering Company

Agriculture

Pharma/Biotech Company

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IBM SPSS Modeler was previously known as SPSS Modeler.

IBM SPSS Modeler customers

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey