Dataiku Data Science Studio vs SAS Enterprise Miner comparison

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Dataiku Logo
9,361 views|7,285 comparisons
100% willing to recommend
SAS Logo
1,119 views|911 comparisons
93% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Dataiku Data Science Studio and SAS Enterprise Miner based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: April 2024).
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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The most valuable feature is the set of visual data preparation tools.""Data Science Studio's data science model is very useful.""Cloud-based process run helps in not keeping the systems on while processes are running.""Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors.""I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person.""The solution is quite stable.""The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."

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"The solution is very good for data mining or any mining issues.""The most valuable feature is the decision tree creation.""The solution is able to handle quite large amounts of data beautifully.""he solution is scalable.""I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks.""Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic.""The setup is straightforward. Deployment doesn't take more than 30 minutes.""Good data management and analytics."

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Cons
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective.""Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days).""In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin.""I find that it is a little slow during use. It takes more time than I would expect for operations to complete.""I think it would help if Data Science Studio added some more features and improved the data model.""There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders.""Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable.""The ability to have charts right from the explorer would be an improvement."

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"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system.""The ease of use can be improved. When you are new it seems a bit complex.""The initial setup is challenging if doing it for the first time.""The product must provide better integration with cloud-native technologies.""The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch.""The visualization of the models is not very attractive, so the graphics should be improved.""The solution needs an easier interface for the user. The user experience isn't so easy for our clients.""The user interface of the solution needs improvement. It needs to be more visual."

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Pricing and Cost Advice
  • "The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
  • More Dataiku Data Science Studio Pricing and Cost Advice →

  • "This solution is for large corporations because not everybody can afford it."
  • "The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
  • "The solution must improve its licensing models."
  • More SAS Enterprise Miner Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Data Science Studio's data science model is very useful.
    Top Answer:I think it would help if Data Science Studio added some more features and improved the data model.
    Top Answer:The use case is data science, and we've deployed Data Science Studio in multiple regions for four environments: dev, preset, pre-production, and production.
    Top Answer:I like the way the product visually shows the data pipeline.
    Top Answer:The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pricing… more »
    Top Answer:The product must provide better integration with cloud-native technologies.
    Ranking
    6th
    Views
    9,361
    Comparisons
    7,285
    Reviews
    1
    Average Words per Review
    190
    Rating
    10.0
    15th
    Views
    1,119
    Comparisons
    911
    Reviews
    2
    Average Words per Review
    310
    Rating
    8.5
    Comparisons
    Also Known As
    Dataiku DSS
    Enterprise Miner
    Learn More
    Overview

    Dataiku Data Science Studio is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently.

    Dataiku Data Science Studio is also known as Dataiku DSS. This solution enables you to discover, share, and reuse code and applications so that you can deliver high-quality projects easily and streamline your path to production. As an enterprise leader, you can leverage the power of AI to confidently make business decisions.

    With Dataiku, an intuitive interface is guaranteed and allows users the ability to access and work with data using a point-and-click method. Dataiku analyzes the data to suggest key transformations. Beyond offering 109 data transformation capabilities, Dataiku also includes pipelines that can be generated in SQL which can thereafter be scheduled for automated recomputation.

    What's more, Dataiku allows you to create more than 20 different kinds of charts and also gives you the ability to deploy them into dashboards or create custom web applications for the use of interactive and sophisticated visualization tools.

    In addition, with Dataiku you have the option of using an in-depth statistical analysis, including but not limited to: curves fitting, univariate and bivariate analysis, principal component analysis, correlation analysis, and statistical tests.

    Dataiku Data Science Studio Consists Of:

    • Data preparation
    • Visualization
    • Machine Learning
    • Data Ops
    • ML Ops
    • Analytic Apps

    With Dataiku Data Science Studio You Can:

    • Integrate any data 10x faster
    • Build and automate sophisticated data pipelines
    • Build and share insights in minutes
    • Perform in-depth statistical analysis
    • Create thousands of models to find the best ones
    • Explore and explain models

    Dataiku Data Science Studio Benefits and Features:

    • Use your favorite languages and tools: You can create code working with tools you are already familiar with in the language you prefer (Python, R, SQL, etc.)
    • Easily reuse and share code: This feature helps you reduce inefficiencies and inconsistent data. Dataiku includes project libraries, allowing teams to centralize and share code. Although it comes pre-loaded with starter code for tasks, it also provides you with the ability to add your own code snippets.
    • Simplify complexities related to connecting to data and configuring computer resources: With this feature, data scientists can execute code in both a containerized and distributed way, while also selecting the runtime environment they want. Dataiku works to maintain those containers as well as shut them down when the job is completed.

    Features Users Find Most Valuable:

    • API
    • Reporting/Analytics
    • Third-Party Integrations
    • Data Import/Export
    • Natural Language Processing
    • Search/Filter
    • Monitoring
    • Workflow Management

    Reviews from Real Users

    PeerSpot users note that Dataiku Data Science Studio has a fantastic interface and is also flexible, intuitive, and stable. One user said "I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person." Another user mentioned “The best feature is the user interface. It allows us to see the visual flows.”

    SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.
    Sample Customers
    BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
    Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Educational Organization13%
    Manufacturing Company8%
    Computer Software Company8%
    REVIEWERS
    Financial Services Firm44%
    Retailer22%
    University22%
    Media Company11%
    VISITORS READING REVIEWS
    Financial Services Firm23%
    University12%
    Educational Organization8%
    Insurance Company7%
    Company Size
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise19%
    Large Enterprise69%
    REVIEWERS
    Small Business21%
    Midsize Enterprise29%
    Large Enterprise50%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise10%
    Large Enterprise70%
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    768,740 professionals have used our research since 2012.

    Dataiku Data Science Studio is ranked 6th in Data Science Platforms while SAS Enterprise Miner is ranked 15th in Data Science Platforms with 13 reviews. Dataiku Data Science Studio is rated 8.2, while SAS Enterprise Miner is rated 7.6. The top reviewer of Dataiku Data Science Studio writes "The model is very useful". On the other hand, the top reviewer of SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". Dataiku Data Science Studio is most compared with Databricks, Alteryx, KNIME, Microsoft Azure Machine Learning Studio and RapidMiner, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and SAS Analytics.

    See our list of best Data Science Platforms vendors.

    We monitor all Data Science Platforms 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.