SAP Predictive Analytics [EOL] vs SAS Enterprise Miner comparison

SAP and SAS are both solutions in the Data Science Platforms category. SAP is ranked #27, while SAS is ranked #23. SAP holds a 1.4% mindshare in Data Science Platforms, compared to SAS’s 1.8% mindshare. Additionally, 100% of SAP users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

SAP Predictive Analytics [EOL]

Read 3 SAP Predictive Analytics [EOL] reviews

783 Views
775 Comparison Views

100% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,532 Views
1,195 Comparison Views

93% willing to recommend

SAP Predictive Analytics [EOL]

SAS Enterprise Miner

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Executive SummaryUpdated on Apr 15, 2026

SAS Enterprise Miner and SAP Predictive Analytics [EOL] compete in the advanced analytics space. SAS Enterprise Miner has an edge in pricing with its transparent cost structure, while SAP Predictive Analytics [EOL] offers greater value through its robust feature set and automation capabilities.

Features: SAS Enterprise Miner provides powerful data mining capabilities, intuitive data preparation, exploration, and model comparison functions. SAP Predictive Analytics [EOL] excels in automation features, including predictive modeling and scoring, with extensive analytics capabilities. The advanced automation in SAP significantly enhances productivity.

Ease of Deployment and Customer Service: SAP Predictive Analytics [EOL] supports simplified cloud-based deployment, easing the implementation process and providing responsive technical support. SAS Enterprise Miner requires a more flexible architecture for deployment but offers reliable customer service with comprehensive support options.

Pricing and ROI: SAS Enterprise Miner offers a favorable cost structure with setup cost efficiency, providing clear ROI through its features and data functionalities. SAP Predictive Analytics [EOL] requires a higher initial investment but offers a quicker and higher ROI due to its superior automation features, balancing cost with performance and return.

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April 2026

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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

SAP Predictive Analytics [EOL]

Ranking in Data Science Platforms

27th

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

SAS Enterprise Miner

Ranking in Data Science Platforms

23rd

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

Mindshare comparison

As of April 2026, in the Data Science Platforms category, the mindshare of SAP Predictive Analytics [EOL] is 1.4%, up from 0.4% compared to the previous year. The mindshare of SAS Enterprise Miner is 1.8%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
SAS Enterprise Miner	1.8%
SAP Predictive Analytics	1.4%
Other	96.8%

Data Science Platforms

Featured Reviews

Gary Cook

Executive at Empowered Analytics

Enables us to forecast and pull trends and has an easy installation

My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

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reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

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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Quotes from Members

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

Pros

"I have found that the solution is very stable."

"The most valuable features are the analytics and reporting."

"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."

"I think the features of the actual ability to forecast and pull trends and correlations has been really good."

"We always purchase SAP support because it is very good."

"SAS internal support is very qualified and if we have any issues, we contact them and trust that they can help."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"Overall it is a good solution."

"Most of the features, especially on the data analysis tool pack, are really good; the way they do clustering and output is great, you can do fairly elaborate outputs, and the results and the ensembles are fantastic."

"Technical support has been good, and when I called them at the start of using the product with some issues they were very helpful."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."

More SAS Enterprise Miner pros

Cons

"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."

"This solution works for acquired data but not live, real-time data."

"The preparation of both the mining and modeling process could be improved. The solution requires data and will reflect data, but the preparation of the data is not useful for end-users; we ended up having to do the preparation in another tool."

"The stability isn't perfect. We have issues with accuracy in some AI forecasting areas, and the accuracy is not as good as the clients need it to be."

"Plus it is prohibitively expensive and is not available with perpetual licensing."

"The product must provide better integration with cloud-native technologies."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

"The license is really expensive. This solution is for large corporations because not everybody can afford it."

"Technical support could be improved."

"The initial setup is challenging if doing it for the first time."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"The pricing is reasonable"

"A free trial version is available for testing out this solution."

"The solution must improve its licensing models."

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"This solution is for large corporations because not everybody can afford it."

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

19%

Construction Company

12%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

Comparisons

KNIME Business Hub vs SAP Predictive Analytics [EOL]

Compared 8% of the time

Saturn Cloud vs SAP Predictive Analytics [EOL]

Compared 7% of the time

IBM SPSS Statistics vs SAP Predictive Analytics [EOL]

Compared 7% of the time

Starburst Galaxy vs SAP Predictive Analytics [EOL]

Compared 6% of the time

Altair RapidMiner vs SAP Predictive Analytics [EOL]

Compared 6% of the time

More SAP Predictive Analytics [EOL] Competitors

KNIME Business Hub vs SAS Enterprise Miner

Compared 13% of the time

Azure Data Lake Analytics vs SAS Enterprise Miner

Compared 8% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 7% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 5% of the time

IBM SPSS Statistics vs SAS Enterprise Miner

Compared 5% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Data Science Platforms

April 2026

Download SAP Predictive Analytics [EOL] product report

Buyer's Guide

Data Mining

March 2026

Download SAS Enterprise Miner product report

Also Known As

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

Enterprise Miner

Overview

SAP Predictive Analytics [EOL] offered a powerful platform for creating predictive models that supported business decision-making by utilizing historical data to anticipate future trends.

SAP Predictive Analytics [EOL] was designed to integrate with existing SAP environments, allowing businesses to leverage their existing data infrastructure. It provided users with intuitive tools to automate data preparation and model management, simplifying complex analytical processes. Data scientists could efficiently build and deploy predictive models to address specific business questions. SAP emphasized ease of deployment and scalability, ensuring the platform met the needs of data-driven enterprises.

What are the key features?

Automated Model Creation: Streamlines the process of generating predictive models, reducing time and effort.
Data Preparation: Simplifies data cleaning and preparation, ensuring high-quality input for analysis.
Seamless Integration: Easily integrates with SAP environments, enhancing data accessibility.

What benefits should users consider in reviews?

Informed Decision-Making: Provides insights that help businesses make data-informed decisions.
Efficiency in Analysis: Reduces the time needed to develop and deploy predictive models.
Scalability: Supports expanding data needs as businesses grow.

In industries like manufacturing and retail, SAP Predictive Analytics [EOL] helped optimize supply chains and inventory management by forecasting demand trends. Financial sector users implemented it to enhance risk analysis and fraud detection models, providing valuable insights for mitigating potential risks.

SAP

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

Sample Customers

mBank

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

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April 2026

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