"The solution is quite stable."
"Data Science Studio's data science model is very useful."
"I was able to apply basic algorithms through just dragging and dropping."
"We have found KNIME valuable when it comes to its visualization."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"Overall KNIME serves its purpose and does a good job."
"The solution is good for teaching, since there is no need to code."
"The product is open-source and therefore free to use."
"From a user-friendliness perspective, it's a great tool."
"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."
"Compared to the other data tools on the market, the user interface can be improved."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"If they had a more structured training model it would be very helpful."
"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"From the point of view of the interface, they can do a little bit better."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
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.”
KNIME is an open-source analytics software used for creating data science that is built on a GUI based workflow, eliminating the need to know code. The solution has an inherent modular workflow approach that documents and stores the analysis process in the same order it was conceived and implemented, while ensuring that intermediate results are always available. KNIME supports Windows, Linux, and Mac operating systems and is suitable for enterprises of all different sizes. With KNIME, you can perform functions ranging from basic I/O to data manipulations, transformations and data mining. It consolidates all the functions of the entire process into a single workflow. The solution covers all main data wrangling and machine learning techniques, and is based on visual programming.
KNIME has many valuable key features. Some of the most useful ones include:
There are many benefits to implementing KNIME. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the KNIME solution.
Benedikt S., CEO at SMH - Schwaiger Management Holding GmbH, explains, “All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function. Technical support has been extremely responsive so far. The solution has a very strong and supportive community that shares information and helps each other troubleshoot. The solution is very stable. The initial setup is pretty simple and straightforward.”
Piotr Ś., Test Engineer at ProData Consult, says, “What I like the most is that it works almost out of the box with Random Forest and other Forest nodes.”
Dataiku Data Science Studio is ranked 8th in Data Science Platforms with 2 reviews while KNIME is ranked 3rd in Data Science Platforms with 16 reviews. Dataiku Data Science Studio is rated 9.6, while KNIME is rated 8.2. The top reviewer of Dataiku Data Science Studio writes "Flexible and intuitive with good stability". On the other hand, the top reviewer of KNIME writes "Allows you to easily tidy up your data, make lots of changes internally, and has good machine learning". Dataiku Data Science Studio is most compared with Databricks, Alteryx, Microsoft Azure Machine Learning Studio, Amazon SageMaker and H2O.ai, whereas KNIME is most compared with Alteryx, RapidMiner, Weka, Microsoft BI and Databricks. See our Dataiku Data Science Studio vs. KNIME report.
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