Oracle Advanced Analytics vs SAS Analytics comparison

Oracle and SAS are both solutions in the Data Mining category. Oracle is ranked #6 with an average rating of 9.0, while SAS is ranked #5 with an average rating of 8.0. Oracle holds a 4.0% mindshare in DM, compared to SAS’s 6.6% mindshare. Additionally, 55% of Oracle users are willing to recommend the solution, compared to 94% of SAS users who would recommend it.

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Oracle Advanced Analytics and SAS Analytics 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 Oracle Advanced Analytics vs. SAS Analytics Report (Updated: December 2024).

Buyer's Guide

Oracle Advanced Analytics vs. SAS Analytics

December 2024

Download the complete report

Helped 824,053 peers since 2012

Categories and Ranking

IBM SPSS Statistics

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 Oracle Advanced Analytics is 4.0%, down from 4.9% compared to the previous year. The mindshare of SAS Analytics is 6.6%, down from 10.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

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.

Read full review

Alejandro Merida

Enterprise Solutions Architect at CONTPAQi

Has efficient predictive analysis capabilities, helping us maintain a secure network environment

Our primary use case for the product is managing and analyzing our business's data lakes, which have accumulated over nearly 40 years The platform's most valuable features are the efficient organization of data and the ability to extract specific insights for predictive analysis. One area for…

Read full review

Tanin U

Assistant Vice President at AEON Thana Sinsap

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.

Read full review

Quotes from Members

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

Pros

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

"It is a modeling tool with helpful automation."

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

"The most valuable feature is its robust statistical analysis capabilities."

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

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

"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."

"The most valuable features are the small learning curve and its ability to hold a lot of data."

More IBM SPSS Statistics pros

"Oracle Advanced Analytics effectively prevents threats and helps maintain a secure network environment."

"When needed, we will work closely with Oracle support and implement their workaround in our application."

"Ability to pull together multiple sources of information."

"The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic."

"The most valuable feature is the ability to handle large data sets."

"The team immediately resolves the issues."

"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."

"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."

"It has improved the level of efficacy and validity of our reports."

"I use it to replicate our entire financial system to verify/duplicate calculations."

"SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency."

"It has also been around for an extremely long time, has a strong history, and good market penetration."

More SAS Analytics pros

Cons

"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."

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

"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."

"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."

"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."

More IBM SPSS Statistics cons

"There are some transactions we have not been able to find through the dashboard."

"One area for product improvement is the user experience, particularly when navigating through screens."

"The performance, scalability and queries should be addressed, as well as the data distribution of certain data techniques."

"Could use some refinement getting things that are not standard cloud applications, but more customized."

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

"This solution should be made more user-friendly."

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

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

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

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

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

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

More SAS Analytics cons

Pricing and Cost Advice

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

"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."

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

"It's quite expensive, but they do a special deal for universities."

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

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

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

"The price of IBM SPSS Statistics could improve."

More IBM SPSS Statistics pricing and cost advice

"The solution is priced well."

"Setup costs were quite reasonable."

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

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

"Licensing was rather straightforward."

"SAS is very expensive."

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

"Our licensing covers the usage for around 50 data analysts."

"Prices were comparable with alternative solutions."

More SAS Analytics pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Data Mining solutions are best for your needs.

See recommendations

824,053 professionals have used our research since 2012.

Comparison Review

it_user7308

Consultant with 51-200 employees

Jun 26, 2013

Oracle Data Mining vs. SAS is like Support Vector Machines vs. Neural Nets

I’m part of a small group of mathematics enthusiasts in Kansas City who meet about once a month on Saturday mornings to drink coffee and discuss mathematics. This past weekend it was my turn to do a presentation to the rest of the group and I chose to speak on the mathematical foundations of the…

Read full review

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

University

19%

Computer Software Company

14%

Government

13%

Manufacturing Company

10%

Financial Services Firm

13%

Computer Software Company

11%

Educational Organization

10%

University

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?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

See all answers

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 result...

See all answers

What needs improvement with Oracle Advanced Analytics?

One area for product improvement is the user experience, particularly when navigating through screens, especially on ...

See all answers

What is your primary use case for Oracle Advanced Analytics?

Our primary use case for the product is managing and analyzing our business's data lakes, which have accumulated over...

See all answers

What advice do you have for others considering Oracle Advanced Analytics?

Oracle Advanced Analytics effectively prevents threats and helps maintain a secure network environment. Experienced p...

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

Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 16% of the time

Alteryx 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 11% of the time

Dataiku vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

No data available

KNIME vs SAS Analytics

Compared 36% 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

Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Oracle Advanced Analytics

December 2024

Download Oracle Advanced Analytics product report

Buyer's Guide

Data Mining

November 2024

Download SAS Analytics product report

Also Known As

SPSS Statistics

OAA

No data available

Learn More

Video not available

IBM

Oracle

Video not available

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.”

Oracle Advanced Analytics 12c delivers parallelized in-database implementations of data mining algorithms and integration with open source R. Data analysts use Oracle Data Miner GUI and R to build and evaluate predictive models and leverage R packages and graphs. Application developers deploy Oracle Advanced Analytics models using SQL data mining functions and R. With the Oracle Advanced Analytics option, Oracle extends the Oracle Database to an sclable analytical platform that mines more data and data types, eliminates data movement, and preserves security to anticipate customer behavior, detect patterns, and deliver actionable insights. Oracle Big Data SQL adds new big data sources and Oracle R Advanced Analytics for Hadoop provides algorithms that run on Hadoop.

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.

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

Orbitz, Marriott, SGS Life Science, Masdar, AlliantEnergy Corporation, British Standards Institute, Skybox Security, Triple PointTechnology, and Coca Cola.

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

Buyer's Guide

Oracle Advanced Analytics vs. SAS Analytics

December 2024

Free Report: Oracle Advanced Analytics vs. SAS Analytics

Find out what your peers are saying about Oracle Advanced Analytics vs. SAS Analytics and other solutions. Updated: December 2024.

DOWNLOAD NOW

824,053 professionals have used our research since 2012.

See our Oracle Advanced Analytics vs. SAS Analytics report.

See our list of best Data Mining vendors.

We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.