Oracle Machine Learning vs. SAS Enterprise Miner

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Oracle Machine Learning
Score 8.0 out of 10
N/A
Oracle Machine Learning (formerly Oracle Advanced Analytics) combines the Oracle database with Oracle Data Miner and SQL as well as R programming language functionality, providing a complete predictive analytics suite.N/A
SAS Enterprise Miner
Score 9.0 out of 10
N/A
SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.N/A
Pricing
Oracle Machine LearningSAS Enterprise Miner
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Oracle Machine LearningSAS Enterprise Miner
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
Oracle Machine LearningSAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Oracle Machine Learning
-
Ratings
SAS Enterprise Miner
8.8
4 Ratings
6% above category average
Connect to Multiple Data Sources00 Ratings8.14 Ratings
Extend Existing Data Sources00 Ratings9.04 Ratings
Automatic Data Format Detection00 Ratings9.34 Ratings
MDM Integration00 Ratings9.02 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Oracle Machine Learning
-
Ratings
SAS Enterprise Miner
8.1
4 Ratings
5% below category average
Visualization00 Ratings7.14 Ratings
Interactive Data Analysis00 Ratings9.14 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Oracle Machine Learning
-
Ratings
SAS Enterprise Miner
8.0
4 Ratings
2% below category average
Interactive Data Cleaning and Enrichment00 Ratings7.84 Ratings
Data Transformations00 Ratings8.24 Ratings
Data Encryption00 Ratings8.12 Ratings
Built-in Processors00 Ratings8.12 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Oracle Machine Learning
-
Ratings
SAS Enterprise Miner
8.8
4 Ratings
5% above category average
Multiple Model Development Languages and Tools00 Ratings7.54 Ratings
Automated Machine Learning00 Ratings9.82 Ratings
Single platform for multiple model development00 Ratings8.54 Ratings
Self-Service Model Delivery00 Ratings9.23 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Oracle Machine Learning
-
Ratings
SAS Enterprise Miner
7.8
4 Ratings
8% below category average
Flexible Model Publishing Options00 Ratings7.04 Ratings
Security, Governance, and Cost Controls00 Ratings8.54 Ratings
Best Alternatives
Oracle Machine LearningSAS Enterprise Miner
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.0 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.0 out of 10
Medium-sized Companies
Posit
Posit
Score 9.6 out of 10
Mathematica
Mathematica
Score 8.2 out of 10
Enterprises
Posit
Posit
Score 9.6 out of 10
Posit
Posit
Score 9.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Oracle Machine LearningSAS Enterprise Miner
Likelihood to Recommend
8.0
(10 ratings)
9.9
(4 ratings)
Support Rating
-
(0 ratings)
10.0
(2 ratings)
User Testimonials
Oracle Machine LearningSAS Enterprise Miner
Likelihood to Recommend
Oracle
OAC doesn't require software to be installed since it is browser based. This allows for easier deployment since a local client software is not required to be installed for each user. OAC can be used for the casual light user who mainly consumes data to the power user who can created sophisticated dashboard with advanced analytics. OAC is not meant to replace Essbase reporting.
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SAS
SAS Enterprise Miner is world-class software for individuals interested in developing reproducible models in a reasonable amount of time. Perhaps the most useful part of SAS Enterprise Miner is the ability to compare models with other models without writing code. The ensemble modeling capabilities is the easiest way to do ensemble modeling I have come across. SAS Enterprise Miner is well-suited for beginning to advanced analysts who know something about advanced analytics. The software is not well-suited for analysts or companies that have little interest in advanced modeling.
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Pros
Oracle
  • Analyzing heaps of data dumped into the machine learning tool.
  • Giving the researcher an insight on which direction to proceed in order to get the desired results.
  • Can help perform a functional analysis before doing a deep dive.
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SAS
  • Enterprise Miner is really visual and lets you do a whole lot without actually going into the detailed options. For decent results, you should really explore the different advanced options though.
  • The recent versions of Miner allow users to use R code in Miner. You can then compare several models and approach to get the best performing model.
  • The resulting data is really well displayed and easy to understand (ex: the lift graph, score ranking, etc.)
  • Miner has the ability to integrate custom SAS code which allows the user to add functionalities that are specific to the project.
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Cons
Oracle
  • As mentioned by others the formatting of reports constantly has issues
  • Once your initial contract terms are up be prepared for a significant increase
  • Pricing needs to be inline with what other competitors are offering
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SAS
  • SAS is not as user friendly as other stats software.
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Support Rating
Oracle
No answers on this topic
SAS
SAS' customer support used to be non-existent many years ago. Today, contacting SAS customer support is great. They are responsible, knowledgable, and seem to have an interest in getting the results right the first time. With that said, Enterprise Miner's online support is weak, probably because the user base is much smaller than other tools.
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Alternatives Considered
Oracle
Sorry this product was not selected by me, but was a legacy install that was upgraded. I see the value in the product, however, I was not involved in the selection process.
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SAS
SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data preparation capabilities compared to the other tools we used.
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Return on Investment
Oracle
  • Our ROI has been great since we have been able to get a birdseye view of our business operations.
  • Shows your areas within your company that needs attention and improvements.
  • Oracle has had a positive impact on all of our business objectives since it provides a clear view of your business operations.
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SAS
  • In our organization, users were using SAS already so the learning curve was really low. Within a few weeks after the implementation, the users were already delivering models developed with SAS Enterprise Miner. It is difficult to talk about ROI as models were already being developed before. It was mostly a change of technology and it was a smooth transition.
  • Going with Enterprise Miner came with migration from desktop use of SAS to a server use of SAS. This created a new role of SAS administrator. This was obviously a cost but as the use of SAS increased greatly, it was expected.
  • From a methodology standpoint, Enterprise Miner helped greatly in the documentation of the model development which was a requirement in a few groups such as the risk groups. Having a visual "GUI-like" approach to development, the flowchart or diagram of the project in Miner was able to give users a good understanding of the approach the analyst took to develop the model.
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ScreenShots