Oracle Advanced Analytics vs SAS Analytics comparison

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Executive Summary

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

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To learn more, read our detailed Data Mining Report (Updated: March 2024).
765,386 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
"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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"SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency.""It has improved the level of efficacy and validity of our reports.""The most valuable feature is the ability to handle large data sets.""The team immediately resolves the issues.""It has also been around for an extremely long time, has a strong history, and good market penetration.""All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team.""It has facilitated timely analysis results with quality work and meaningful output.""It is able to connect to all major platforms, and all the smaller platforms that I have come across."

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

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"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.""This solution should be made more user-friendly.""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.""​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.""There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."

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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
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    Top Answer:The team immediately resolves the issues.
    Top Answer:They could enhance the AI capabilities of the product as the landscape is evolving with AI playing a significant role in analytics.
    Top Answer:We use SAS Analytics in the area of Business Intelligence (BI), particularly for analyzing data and generating reports.
    Ranking
    7th
    out of 18 in Data Mining
    Views
    644
    Comparisons
    415
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    5th
    out of 18 in Data Mining
    Views
    1,023
    Comparisons
    808
    Reviews
    1
    Average Words per Review
    278
    Rating
    10.0
    Comparisons
    Also Known As
    OAA
    Learn More
    Overview

    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
    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
    VISITORS READING REVIEWS
    Government15%
    Computer Software Company13%
    University13%
    Manufacturing Company13%
    REVIEWERS
    Financial Services Firm30%
    Healthcare Company20%
    Insurance Company10%
    Retailer10%
    VISITORS READING REVIEWS
    Financial Services Firm12%
    University11%
    Educational Organization9%
    Comms Service Provider9%
    Company Size
    REVIEWERS
    Small Business67%
    Midsize Enterprise22%
    Large Enterprise11%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise13%
    Large Enterprise66%
    REVIEWERS
    Small Business31%
    Midsize Enterprise8%
    Large Enterprise62%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise10%
    Large Enterprise70%
    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.
    765,386 professionals have used our research since 2012.

    Oracle Advanced Analytics is ranked 7th in Data Mining while SAS Analytics is ranked 5th in Data Mining with 10 reviews. Oracle Advanced Analytics is rated 8.0, while SAS Analytics is rated 9.2. The top reviewer of Oracle Advanced Analytics writes "Helpful technical support, but performance and queries should be addressed". On the other hand, the top reviewer of SAS Analytics writes "Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks". Oracle Advanced Analytics is most compared with IBM SPSS Statistics, Weka and KNIME, whereas SAS Analytics is most compared with KNIME, IBM SPSS Statistics, Weka and SAS Enterprise Miner.

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