IBM SPSS Modeler vs Oracle Advanced Analytics vs SAS Analytics comparison

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1,725 views|1,363 comparisons
85% willing to recommend
Oracle Logo
618 views|407 comparisons
50% willing to recommend
SAS Logo
979 views|783 comparisons
94% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between IBM SPSS Modeler, Oracle Advanced Analytics, and SAS Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.
To learn more, read our detailed Data Mining Report (Updated: March 2024).
768,924 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"We use analytics with the visual modeling capability to leverage productivity improvements.""We have full control of the data handling process.""It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms.""We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python.""Automation is great and this product is very organized.""We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive.""It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler.""I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."

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"When needed, we will work closely with Oracle support and implement their workaround in our application.""The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic.""Ability to pull together multiple sources of information."

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"The technical support is okay.""They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy.""I use it to replicate our entire financial system to verify/duplicate calculations.""Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features.""It has improved the level of efficacy and validity of our reports.""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.""SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency."

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Cons
"The time series should be improved.""Unstructured data is not appropriate for SPSS Modeler.""The product does not have a search function for tags.""I would like see more programming languages added, like MATLAB. That would be better.""The challenge for the very technical data scientists: It is constraining for them.​""Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler.""​Initial setup of the software was complex, because of our own problems within the government.""The integration with sources and visualisation needs some improvement. The scalability needs improvement."

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"The performance, scalability and queries should be addressed, as well as the data distribution of certain data techniques.""There are some transactions we have not been able to find through the dashboard.""Could use some refinement getting things that are not standard cloud applications, but more customized."

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"The installation could also be easier, and the price could be better.""​Support at universities used to be limited, but I hear this is changing.​""The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities.""I would like to see their interface to R added to either Base SAS or SAS Analytics.""This solution should be made more user-friendly.""The natural language querying and automated preparation of dashboards should be improved.""One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist.""They could enhance the AI capabilities of the product."

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Pricing and Cost Advice
  • "Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."
  • "If you are in a university and the license is free then you can use the tool without any charges, which is good."
  • "It is a huge increase to time savings."
  • "The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."
  • "When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."
  • "It got us a good amount of money with quick and efficient modeling."
  • "$5,000 annually."
  • "This tool, being an IBM product, is pretty expensive."
  • More IBM SPSS Modeler Pricing and Cost Advice →

  • "It is relatively expensive. It is not an easy software to afford."
  • "​Setup costs were quite reasonable."
  • "Prices were comparable with alternative solutions."
  • "Licensing was rather straightforward."
  • "​The cost for SAS Business Intelligence can prove to be a little prohibitive.​"
  • "I think that the cost-benefit ratio is okay."
  • "SAS is very expensive."
  • "Our licensing covers the usage for around 50 data analysts."
  • More SAS Analytics Pricing and Cost Advice →

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    Comparison Review
    Anonymous User
    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 Support Vector Machine algorithm in Oracle Data Mining. While I wasn’t surprised that some in the group had a better handle on Vapnik-Chervonenkis theory than I and gently “guided” me a few times, I was somewhat surprised at their positive reaction to my characterization of the “Oracle” approach to data mining in contrast with the “SAS” approach. While gross simplifications are always “gross”, here is my take on what I believe to be very different philosophies. Let’s use classification as an example since we’re talking about SVMs. I think of the “SAS” approach to be similar to that of a “statistician” or classic data scientist. That is, there is a desire to understand the algorithm in context of the data set. The main objective is to identify and understand the source(s) of error in the model and to characterize the algorithm through the use various coefficients and ratios. A good deal of effort is spent in the evaluation process of the algorithm and in understanding the impact of different choices in methodology. The SAS perspective emphasizes understanding the data preparation and the algorithm. The more detail, the better. The “Oracle” approach to data mining is characterized by a… Read more →
    Questions from the Community
    Top Answer:Compared to other tools, the product works much easier to analyze data without coding.
    Top Answer:The platform's cloud version needs improvements. The process to access workflow could be user-friendly. It could be… more »
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    Top Answer:SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer… more »
    Top Answer:There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports.
    Top Answer:Our use case involves leveraging SAS Analytics to support experts in various departments such as collections and… more »
    Ranking
    4th
    out of 18 in Data Mining
    Views
    1,725
    Comparisons
    1,363
    Reviews
    6
    Average Words per Review
    372
    Rating
    7.3
    7th
    out of 18 in Data Mining
    Views
    618
    Comparisons
    407
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    5th
    out of 18 in Data Mining
    Views
    979
    Comparisons
    783
    Reviews
    2
    Average Words per Review
    359
    Rating
    8.5
    Comparisons
    Also Known As
    SPSS Modeler
    OAA
    Learn More
    IBM
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    Overview

    IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

    Buy
    https://www.ibm.com/products/spss-modeler/pricing
     
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    https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947


    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
    Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey
    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
    Top Industries
    REVIEWERS
    University23%
    Financial Services Firm17%
    Manufacturing Company14%
    Government9%
    VISITORS READING REVIEWS
    Educational Organization16%
    Financial Services Firm10%
    Computer Software Company9%
    University8%
    VISITORS READING REVIEWS
    Government15%
    Manufacturing Company13%
    University13%
    Computer Software Company12%
    REVIEWERS
    Financial Services Firm27%
    Healthcare Company18%
    Insurance Company9%
    Retailer9%
    VISITORS READING REVIEWS
    Financial Services Firm12%
    University10%
    Computer Software Company10%
    Educational Organization9%
    Company Size
    REVIEWERS
    Small Business19%
    Midsize Enterprise10%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business22%
    Midsize Enterprise14%
    Large Enterprise64%
    REVIEWERS
    Small Business70%
    Midsize Enterprise20%
    Large Enterprise10%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise11%
    Large Enterprise68%
    REVIEWERS
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise11%
    Large Enterprise69%
    Buyer's Guide
    Data Mining
    March 2024
    Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: March 2024.
    768,924 professionals have used our research since 2012.