SAS Analytics vs SAS Enterprise Miner comparison

SAS Analytics and SAS Enterprise Miner are both solutions in the Data Mining category. SAS Analytics is ranked #5 with an average rating of 8.0, while SAS Enterprise Miner is ranked #7 with an average rating of 8.5. SAS Analytics holds a 6.9% mindshare in DM, compared to SAS Enterprise Miner’s 4.0% mindshare. Additionally, 94% of SAS Analytics users are willing to recommend the solution, compared to 93% of SAS Enterprise Miner users who would recommend it.

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Executive Summary

We performed a comparison between SAS Analytics and SAS Enterprise Miner based on real PeerSpot user reviews.

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed SAS Analytics vs. SAS Enterprise Miner Report (Updated: October 2024).

Buyer's Guide

SAS Analytics vs. SAS Enterprise Miner

October 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Mining category, the mindshare of IBM SPSS Statistics is 14.5%, up from 12.8% compared to the previous year. The mindshare of SAS Analytics is 6.9%, down from 10.2% compared to the previous year. The mindshare of SAS Enterprise Miner is 4.0%, down from 5.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Sep 21, 2023

Enhancing survey analysis that provides valued insightfulness

I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…

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Tanin U

Assistant Vice President at AEON Thana Sinsap

Jan 25, 2024

Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks

SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency. While our current setup operates smoothly, certain partners still rely on another platform, specifically the virtualization dashboard. I believe it's a significant improvement compared to the traditional approach I've been using for the past ten years. Previously, when management had inquiries, they would create documents or memos, and IT would then track down the data, interpret it, and provide feedback. This process involved explaining the data structure, database, and definitions in the data warehouse. Now, with SAS Analytics, the workflow is much smoother and faster. IT is more streamlined, allowing for quicker access to data, and managers can directly access and utilize the sales reports.

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reviewer1352853

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

Aug 25, 2023

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

"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."

"IBM SPSS Statistics depends on AI."

"SPSS is quite robust and quicker in terms of providing you the output."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"It offers very good visualization."

"Most of the product features are good but I particularly like the linear regression analysis."

"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."

"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."

More IBM SPSS Statistics pros

"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."

"The team immediately resolves the issues."

"It's very easy to use once you learn it."

"It is able to connect to all major platforms, and all the smaller platforms that I have come across."

"I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app."

"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."

"The technical support is okay."

"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."

More SAS Analytics pros

"The most valuable feature is the decision tree creation."

"he solution is scalable."

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

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

"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."

"The solution is very good for data mining or any mining issues."

"I like the way the product visually shows the data pipeline."

"Good data management and analytics."

More SAS Enterprise Miner pros

Cons

"In some cases, the product takes time to load a large dataset. They could improve this particular area."

"The statistics should be more self-explanatory with detailed automated reports."

"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."

"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."

"The reports could be better."

"IBM SPSS Statistics does not keep you close to your data like KNIME."

"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."

More IBM SPSS Statistics cons

"They could enhance the AI capabilities of the product."

"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."

"I would like to see their interface to R added to either Base SAS or SAS Analytics."

"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."

"Support at universities used to be limited, but I hear this is changing."

"The installation could also be easier, and the price could be better."

"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."

"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."

More SAS Analytics cons

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

"Virtualization could be much better."

"The visualization of the models is not very attractive, so the graphics should be improved."

"Technical support could be improved."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"The user interface of the solution needs improvement. It needs to be more visual."

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

"The solution is much more complex than other options."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"The price of IBM SPSS Statistics could improve."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"The price of this solution is a little bit high, which was a problem for my company."

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

"I rate the tool's pricing a five out of ten."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"More affordable training for new staff members."

"We think that IBM SPSS is expensive for this function."

More IBM SPSS Statistics pricing and cost advice

"SAS is very expensive."

"It is relatively expensive. It is not an easy software to afford."

"The pricing tends to be higher, and there are additional expenses involved."

"I think that the cost-benefit ratio is okay."

"The cost for SAS Business Intelligence can prove to be a little prohibitive."

"Licensing was rather straightforward."

"Prices were comparable with alternative solutions."

"I rate the product’s pricing a one out of ten."

More SAS Analytics pricing and cost advice

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

"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."

"The solution must improve its licensing models."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

University

10%

Computer Software Company

Manufacturing Company

Computer Software Company

13%

Financial Services Firm

13%

Educational Organization

10%

University

10%

Financial Services Firm

25%

University

12%

Educational Organization

11%

Insurance Company

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.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Statistics?

While the pricing of the product may be higher, the accompanying service and features justify the investment. However...

See all answers

What needs improvement with IBM SPSS Statistics?

In some cases, the product takes time to load a large dataset. They could improve this particular area.

See all answers

What do you like most about SAS Analytics?

I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile...

See all answers

What needs improvement with SAS Analytics?

The natural language querying and automated preparation of dashboards should be improved. The cost and accessibility ...

See all answers

What is your primary use case for SAS Analytics?

This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.

See all answers

What do you like most about SAS Enterprise Miner?

I like the way the product visually shows the data pipeline.

See all answers

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...

See all answers

What needs improvement with SAS Enterprise Miner?

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

See all answers

Comparisons

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

Dataiku vs IBM SPSS Statistics

Compared 4% of the time

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KNIME vs SAS Analytics

Compared 38% of the time

Weka vs SAS Analytics

Compared 21% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 14% of the time

More SAS Analytics Competitors

SAS Visual Analytics vs SAS Enterprise Miner

Compared 42% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 22% of the time

RapidMiner vs SAS Enterprise Miner

Compared 13% of the time

KNIME vs SAS Enterprise Miner

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner

Compared 12% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

October 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Data Mining

October 2024

Download SAS Analytics product report

Buyer's Guide

Data Mining

October 2024

Download SAS Enterprise Miner product report

Also Known As

SPSS Statistics

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Enterprise Miner

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IBM

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SAS

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.

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.

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

Aegon, Alberta Parks, Amway China, Axel Springer, Bank of America, Belgium Special Tax, CAP Index, CareSource, CBE Group, Cemig, Center for Responsible Lending, CESCE, Ceska sporitelna, Chantecler, Chico's, Chubb Group of Insurance Companies, CIGNA Thailand, City of Wiesbaden, Germany, Confused.com, Creditreform, Des Moines Area Community College, Deutsche Lufthansa, Directorate of Economics and Statistics, DIRECTV, Dow Chemical Company, Dow Chemical Company, Dun & Bradstreet, EDF Energy, Electrabel GDF SUEZ, ERGO Insurance Group, Erste Bank Croatia, Farmers Mutual Group, Finnair, Florida Department of Corrections, Geneia, Generali Hellas, Genting Malaysia Berhad, Grameenphone, Grandi Salumifici Italiani, HealthPartners, Highmark, Hong Kong Efficiency Unit, HP, Hyundai Securities, Illinois Department of Healthcare and Family ServicesInc Research, ING-DiBa, Institut Pertanian Bogor, InterContinental Hotels Group (IHG), IOM, Kelley Blue Book, Lenovo, Lillebaelt Hospital, Los Angeles County, Maspex Wadowice Group, National Bank of Greece, New Zealand Ministry of Health, New Zealand Ministry of Social Development, Nippon Paper, NMIMS, North Carolina Department of Transportation, North Carolina Office of Information Technology Services, Northern Virginia Electric Cooperative (NOVEC), Oberweis Dairy, ODEC, Ohio Mutual Insurance Group, Oklahoma State University, OneBeacon, Orange Business Services, Orange County Child Support Services, Organic, Orlando Magic, OTP Bank, Plano Independent School District, Project Odyssey, Royal Society for the Protection of Birds, RSA Canada, SCAD, Scotiabank, Singapore National Library Board, Sobeys Inc., SRA International, Staples, Statistics Estonia, Swisscom, SymphonyIRI Group, Telecom Italia, Telef‹nica O2, Town of Cary, Transitions Optical, TrueCar, Turkcell Superonline, UniCredit Bank Serbia, University of Alabama, University of Missouri, USDA National Agricultural Statistics Service

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

Buyer's Guide

SAS Analytics vs. SAS Enterprise Miner

October 2024

Free Report: SAS Analytics vs. SAS Enterprise Miner

Find out what your peers are saying about SAS Analytics vs. SAS Enterprise Miner and other solutions. Updated: October 2024.

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