We performed a comparison between KNIME and TIBCO Data Science based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data."
"I was able to apply basic algorithms through just dragging and dropping."
"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."
"Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"It's a very powerful and simple tool to use."
"Since KNIME is a no-code platform, it is easy to work with."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"The most valuable feature is the performance."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
"The most valuable feature is the ease of setting up visualizations."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."
"To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."
"The ability to handle large amounts of data and performance in processing need to be improved."
"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."
"I would prefer to have more connectivity."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"The scripting for customization could be improved."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"I would like the visualization for the map of countries to be more easily configurable."
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KNIME is ranked 4th in Data Science Platforms with 50 reviews while TIBCO Data Science is ranked 25th in Data Science Platforms. KNIME is rated 8.2, while TIBCO Data Science is rated 7.6. The top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". On the other hand, the top reviewer of TIBCO Data Science writes "A straightforward initial setup and good reporting but needs better documentation". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Dataiku Data Science Studio, whereas TIBCO Data Science is most compared with TIBCO Statistica, MathWorks Matlab, Amazon SageMaker and Dataiku Data Science Studio.
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