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IBM ILOG CPLEX Optimization Studio vs. SAS Enterprise Miner

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM ILOG CPLEX Optimization Studio

    Score9.7 out of 10
    N/AIBM® ILOG® CPLEX® Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models using mathematical and constraint programming.

    $285

    per month per user

    SAS Enterprise Miner

    Score9 out of 10
    N/ASAS 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
    IBM ILOG CPLEX Optimization StudioSAS Enterprise Miner
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM ILOG CPLEX Optimization StudioSAS Enterprise Miner
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Features
    IBM ILOG CPLEX Optimization StudioSAS Enterprise Miner
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM ILOG CPLEX Optimization Studio and SAS Enterprise Miner
    Feature
    IBM ILOG CPLEX Optimization Studio
    8.0
    2 Ratings
    4% below category average
    SAS Enterprise Miner
    8.8
    4 Ratings
    5% above category average
    Connect to Multiple Data Sources9.02 Ratings8.14 Ratings
    Extend Existing Data Sources7.02 Ratings9.04 Ratings
    Automatic Data Format Detection8.02 Ratings9.34 Ratings
    MDM Integration8.02 Ratings9.02 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM ILOG CPLEX Optimization Studio and SAS Enterprise Miner
    Feature
    IBM ILOG CPLEX Optimization Studio
    10.0
    2 Ratings
    17% above category average
    SAS Enterprise Miner
    8.1
    4 Ratings
    4% below category average
    Visualization10.02 Ratings7.14 Ratings
    Interactive Data Analysis10.02 Ratings9.14 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM ILOG CPLEX Optimization Studio and SAS Enterprise Miner
    Feature
    IBM ILOG CPLEX Optimization Studio
    7.3
    2 Ratings
    11% below category average
    SAS Enterprise Miner
    8.0
    4 Ratings
    2% below category average
    Interactive Data Cleaning and Enrichment5.01 Ratings7.84 Ratings
    Data Transformations7.01 Ratings8.24 Ratings
    Data Encryption8.02 Ratings8.12 Ratings
    Built-in Processors9.02 Ratings8.12 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM ILOG CPLEX Optimization Studio and SAS Enterprise Miner
    Feature
    IBM ILOG CPLEX Optimization Studio
    8.0
    2 Ratings
    6% below category average
    SAS Enterprise Miner
    8.8
    4 Ratings
    4% above category average
    Multiple Model Development Languages and Tools10.02 Ratings7.54 Ratings
    Automated Machine Learning5.01 Ratings9.82 Ratings
    Single platform for multiple model development8.02 Ratings8.54 Ratings
    Self-Service Model Delivery9.01 Ratings9.23 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM ILOG CPLEX Optimization Studio and SAS Enterprise Miner
    Feature
    IBM ILOG CPLEX Optimization Studio
    10.0
    2 Ratings
    16% above category average
    SAS Enterprise Miner
    7.8
    4 Ratings
    9% below category average
    Flexible Model Publishing Options10.02 Ratings7.04 Ratings
    Security, Governance, and Cost Controls10.02 Ratings8.54 Ratings
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    IBM ILOG CPLEX Optimization StudioSAS Enterprise Miner
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    Anaconda
    Score8.8 out of 10
    Anaconda
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    Enterprises
    IBM Watson Studio
    Score10 out of 10
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    Score10 out of 10
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    User Ratings
    IBM ILOG CPLEX Optimization StudioSAS Enterprise Miner
    Likelihood to Recommend
    9.0
    (2 ratings)
    9.9
    (4 ratings)
    Usability
    9.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    7.0
    (1 ratings)
    10.0
    (2 ratings)
    User Testimonials
    IBM ILOG CPLEX Optimization StudioSAS Enterprise Miner
    Likelihood to Recommend
    IBM
    It is well suited for solving large-sized, mixed-integer, and integer programming problems. Now, the new version supports for Multi-Objective optimization along with some new algorithms such as Benders Decomposition. It is less appropriate for quadratic programming problems where the objective function is the product of multiple variables. However, it's very easy to code any problem.
    Read full review
    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.
    Incentivized
    Read full review
    Pros
    IBM
    • Linear Programming
    • Mixed-Integer Linear Programming
    • Non-Linear Convex-Optimization
    • Visualization
    • Shadow Price Analysis
    • Parameter Tuning
    Read full review
    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.
    Incentivized
    Read full review
    Cons
    IBM
    • Data handling from different sources like Note Pad, etc.
    • Large size of MILP problems.
    • Various parameters to set.
    Read full review
    SAS
    • SAS is not as user friendly as other stats software.
    Incentivized
    Read full review
    Usability
    IBM
    It's nice to use and with good optimization.
    Read full review
    SAS
    No answers on this topic
    Support Rating
    IBM
    Honestly, to say, I never contacted CPLEX but used its forum to know/clarify any issues I faced.
    Read full review
    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.
    Incentivized
    Read full review
    Alternatives Considered
    IBM
    IBM CPLEX Optimization Studio covers wide range of problems in comparison to Gurobi and also offers a number of visualization tools for results analysis. It has better customization and parameter tuning options in comparison to Gurobi. It offers various API integrations such as Python, Java and C++ which is not the case with Gurobi.
    Read full review
    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.
    Incentivized
    Read full review
    Return on Investment
    IBM
    • Faster computation leading to better internal customer relations
    • Able to solve high variable problems with ease
    • Anomaly detection became easier within business
    Read full review
    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.
    Incentivized
    Read full review
    ScreenShots