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IBM Smart Analytics vs SAS Enterprise Miner comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

IBM Smart Analytics
Ranking in Data Mining
8th
Average Rating
7.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
SAS Enterprise Miner
Ranking in Data Mining
7th
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
13
Ranking in other categories
Data Science Platforms (24th)
 

Mindshare comparison

As of October 2025, in the Data Mining category, the mindshare of IBM Smart Analytics is 1.4%, up from 0.8% compared to the previous year. The mindshare of SAS Enterprise Miner is 5.1%, up from 4.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Mining Market Share Distribution
ProductMarket Share (%)
SAS Enterprise Miner5.1%
IBM Smart Analytics1.4%
Other93.5%
Data Mining
 

Featured Reviews

RH
Adding LA on top of a well deployed & working Tivoli Framework opens up a flood of native logged data points. The visual presentation layer of LA is less than cutting edge.
The IBM monitoring software products (Tivoli) are not easy to instrument and require many separate pieces of the total framework to be operationally functional and useable. That said, adding LA on top of a well deployed & working Tivoli Framework opens up a flood of native logged data points for unstructured search & query. My team had a special need to implement custom alerting on 10s of thousands of MQ channels in a short amount of time, and the traditional approach (also w a Tivoli product) would have been very costly (labor) and time consuming (requiring individual app review). As an alternative, we had a new event stream create to track all MQ channels to generate logs and then used LA to visualize the behavior trends for review, reporting and eventually alerting. The effort took longer than I hoped ~6 months, but the traditional approach would have taken 2+ yrs to review and implement app by app.
reviewer1352853 - PeerSpot reviewer
A stable product that is easy to deploy and can be used for structured and unstructured data mining
We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
27%
Educational Organization
12%
University
12%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise4
Large Enterprise7
 

Also Known As

Smart Analytics
Enterprise Miner
 

Overview

 

Sample Customers

WIdO AOK, EEKA Fashion, SSGC, GS Retail
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Find out what your peers are saying about Knime, IBM, Weka and others in Data Mining. Updated: October 2025.
869,771 professionals have used our research since 2012.