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IBM SPSS Statistics vs SAS Enterprise Miner comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
8.7
IBM SPSS Statistics delivers 50% ROI by streamlining data analysis, saving time and money for organizations and universities.
No sentiment score available
 

Customer Service

Sentiment score
6.6
IBM SPSS Statistics users experience varied customer service, generally finding it good; some appreciate prompt assistance, others rarely need support.
No sentiment score available
 

Scalability Issues

Sentiment score
6.5
Users report mixed scalability with IBM SPSS, affected by dataset size, infrastructure, and comparisons to competitors like SAS.
Sentiment score
6.7
SAS Enterprise Miner is scalable with potential cost increases; users generally find it satisfactory except with very large datasets.
 

Stability Issues

Sentiment score
7.6
IBM SPSS Statistics is reliable, handling large datasets well, though minor issues may occur with low RAM environments.
Sentiment score
7.0
SAS Enterprise Miner 14.3 is stable, highly rated, compatible with open-source, yet may need monthly restarts for consistency.
 

Room For Improvement

IBM SPSS Statistics needs improvements in visualization, pricing, interface, integration, documentation, and automation for better user experience.
 

Setup Cost

IBM SPSS Statistics is costly, with advanced models up to $7,000, though discounts exist for educational and developing regions.
SAS Enterprise Miner's high costs and complex licensing drive users towards more flexible, cost-effective alternatives like R.
 

Valuable Features

IBM SPSS Statistics offers a user-friendly interface, robust analysis features, and flexible data handling for comprehensive statistical projects.
 

Categories and Ranking

IBM SPSS Statistics
Ranking in Data Mining
3rd
Ranking in Data Science Platforms
9th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
37
Ranking in other categories
No ranking in other categories
SAS Enterprise Miner
Ranking in Data Mining
7th
Ranking in Data Science Platforms
18th
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
13
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of December 2024, in the Data Mining category, the mindshare of IBM SPSS Statistics is 15.1%, up from 12.7% compared to the previous year. The mindshare of SAS Enterprise Miner is 4.2%, down from 5.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Mining
 

Featured Reviews

Md Masudul Hassan - PeerSpot reviewer
Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts
I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.
SP
Good stability, very good data analysis tool pack and excellent documentation
The solution should be faster. Virtualization could be much better. The solution could add some freeware. The text analytics, for example, aren't there in the VSL version. It requires a separate license. It should be included in the main solution's license as it's a basic requirement. It's shouldn't cost extra.
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
9%
University
8%
Manufacturing Company
8%
Financial Services Firm
25%
University
13%
Educational Organization
8%
Insurance Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive product, despite being good.
What needs improvement with IBM SPSS Statistics?
IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the resulting file and annotate your trail of evidence. It takes you further from your dat...
What do you like most about SAS Enterprise Miner?
I like the way the product visually shows the data pipeline.
What is your experience regarding pricing and costs for SAS Enterprise Miner?
The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pric...
What needs improvement with SAS Enterprise Miner?
The product must provide better integration with cloud-native technologies.
 

Also Known As

SPSS Statistics
Enterprise Miner
 

Learn More

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Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Find out what your peers are saying about IBM SPSS Statistics vs. SAS Enterprise Miner and other solutions. Updated: November 2024.
824,053 professionals have used our research since 2012.