"Data Science Studio's data science model is very useful."
"The solution is quite stable."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"The data science, collaboration, and IDN are very, very strong."
"RapidMiner is very easy to use."
"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."
"I think it would help if Data Science Studio added some more features and improved the data model."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"In the Mexican or Latin American market, it's kind of pricey."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
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:
With Dataiku Data Science Studio You Can:
Dataiku Data Science Studio Benefits and Features:
Features Users Find Most Valuable:
Reviews from Real Users
IT Central Station 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.”
RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.
Dataiku Data Science Studio is ranked 8th in Data Science Platforms with 2 reviews while RapidMiner is ranked 6th in Data Science Platforms with 5 reviews. Dataiku Data Science Studio is rated 9.6, while RapidMiner is rated 9.0. The top reviewer of Dataiku Data Science Studio writes "Flexible and intuitive with good stability". On the other hand, the top reviewer of RapidMiner writes "Extensive features, Turbo Prep, Auto ML, good GUI and good stability". Dataiku Data Science Studio is most compared with Databricks, Alteryx, Microsoft Azure Machine Learning Studio, Amazon SageMaker and IBM Watson Studio, whereas RapidMiner is most compared with KNIME, Alteryx, Microsoft Azure Machine Learning Studio, Tableau and SAS Enterprise Miner. See our Dataiku Data Science Studio vs. RapidMiner report.
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.