IBM SPSS Modeler vs. SAS Enterprise Miner

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
SAS Enterprise Miner
Score 8.2 out of 10
N/A
SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.N/A
Pricing
IBM SPSS ModelerSAS Enterprise Miner
Editions & Modules
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
No answers on this topic
Offerings
Pricing Offerings
IBM SPSS ModelerSAS Enterprise Miner
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
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 SPSS ModelerSAS Enterprise Miner
Considered Both Products
IBM SPSS Modeler

No answer on this topic

SAS Enterprise Miner
Chose SAS Enterprise Miner
SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data …
Top Pros
Top Cons
Features
IBM SPSS ModelerSAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Modeler
-
Ratings
SAS Enterprise Miner
8.8
5 Ratings
4% above category average
Connect to Multiple Data Sources00 Ratings8.15 Ratings
Extend Existing Data Sources00 Ratings9.05 Ratings
Automatic Data Format Detection00 Ratings9.35 Ratings
MDM Integration00 Ratings9.03 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM SPSS Modeler
-
Ratings
SAS Enterprise Miner
8.1
5 Ratings
4% below category average
Visualization00 Ratings7.15 Ratings
Interactive Data Analysis00 Ratings9.25 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM SPSS Modeler
-
Ratings
SAS Enterprise Miner
8.0
5 Ratings
3% below category average
Interactive Data Cleaning and Enrichment00 Ratings7.85 Ratings
Data Transformations00 Ratings8.25 Ratings
Data Encryption00 Ratings8.13 Ratings
Built-in Processors00 Ratings8.13 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM SPSS Modeler
-
Ratings
SAS Enterprise Miner
8.8
5 Ratings
3% above category average
Multiple Model Development Languages and Tools00 Ratings7.55 Ratings
Automated Machine Learning00 Ratings9.93 Ratings
Single platform for multiple model development00 Ratings8.65 Ratings
Self-Service Model Delivery00 Ratings9.24 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
IBM SPSS Modeler
-
Ratings
SAS Enterprise Miner
7.8
5 Ratings
9% below category average
Flexible Model Publishing Options00 Ratings7.05 Ratings
Security, Governance, and Cost Controls00 Ratings8.55 Ratings
Best Alternatives
IBM SPSS ModelerSAS Enterprise Miner
Small Businesses
Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.2 out of 10
Mathematica
Mathematica
Score 8.2 out of 10
Enterprises
Alteryx
Alteryx
Score 9.0 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerSAS Enterprise Miner
Likelihood to Recommend
10.0
(6 ratings)
9.9
(5 ratings)
Support Rating
10.0
(1 ratings)
10.0
(2 ratings)
User Testimonials
IBM SPSS ModelerSAS Enterprise Miner
Likelihood to Recommend
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.
Read full review
SAS
SAS Enterprise Miner is world-class software for individuals interested in developing reproducible models in a reasonable amount of time. Perhaps the most useful part of SAS Enterprise Miner is the ability to compare models with other models without writing code. The ensemble modeling capabilities is the easiest way to do ensemble modeling I have come across. SAS Enterprise Miner is well-suited for beginning to advanced analysts who know something about advanced analytics. The software is not well-suited for analysts or companies that have little interest in advanced modeling.
Read full review
Pros
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.
Read full review
SAS
  • Enterprise Miner is really visual and lets you do a whole lot without actually going into the detailed options. For decent results, you should really explore the different advanced options though.
  • The recent versions of Miner allow users to use R code in Miner. You can then compare several models and approach to get the best performing model.
  • The resulting data is really well displayed and easy to understand (ex: the lift graph, score ranking, etc.)
  • Miner has the ability to integrate custom SAS code which allows the user to add functionalities that are specific to the project.
Read full review
Cons
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.
Read full review
SAS
  • With large data sets, SAS Enterprise Miner sometimes takes a long time to run. Sometimes you have to just leave your computer running while Enterprise Miner does its thing.
  • If you want complete control over the modeling framework, you have to take what Enterprise Miner does and customize it. SAS seems to be working hard on making things easier to customize, but it's not completely there yet.
  • The graphic capabilities of SAS Enterprise Miner leave a lot to be desired, especially in the era of self-service business intelligence software.
Read full review
Support Rating
IBM
The online support board is helpful and the free add ons are incredibly appreciated.
Read full review
SAS
I have contacted SAS twice in the past year and they have been super responsive both times. They solved my problem. I am also registered for an in-person class next month and they called today to tell me that it will be an online-only session. They apologized for the change and registered me for the online version. Super helpful!
Read full review
Alternatives Considered
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.
Read full review
SAS
SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data preparation capabilities compared to the other tools we used.
Read full review
Return on Investment
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.
Read full review
SAS
  • SAS Enterprise Miner is a positive ROI in the sense that it saves a ton of time coding.
  • SAS Enterprise Miner is a negative ROI in that it's expensive, and perhaps makes analysts brainless.
Read full review
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.