Dec 30, 2019
The main difference lies in the community that has KNIME because the additional modules serve a multitude of different jobs from image processing, management of ssh file systems to chemical molecule calculations.
IBM SPSS Modeler and KNIME are leading contenders in the data analytics field, with KNIME often favored due to its advanced integration capabilities and lower cost, making it appealing for enterprises seeking customization.
Features: IBM SPSS Modeler provides user-friendly statistical modeling with pre-built algorithms and automation for data mining. It's ideal for beginners focusing on statistical analysis and predictive modeling. KNIME shines with its open-source framework, offering flexibility, extensive data blending, machine learning support, and seamless integration with other technologies, making it a robust choice for complex analytical workflows.
Room for Improvement: IBM SPSS Modeler could enhance its visual modeling capabilities and expand its data visualization tools to meet industry standards. It's also seen as less flexible compared to open-source alternatives. KNIME could improve by offering more direct professional support options, as its reliance on community resources might not suit every user. Additionally, simplifying the onboarding process for new users could make it more accessible.
Ease of Deployment and Customer Service: IBM SPSS Modeler allows a straightforward deployment process within IBM ecosystems and benefits from professional support. KNIME offers deployment across diverse environments with strong community support and flexible integration capabilities, ideal for tech-savvy teams.
Pricing and ROI: IBM SPSS Modeler typically involves higher costs, providing tailored support and faster ROI in structured settings. KNIME, being open source, presents a low-cost alternative, appealing to startups aiming to minimize expenses. Both tools can deliver high ROI, but KNIME's budget-friendly approach makes it more accessible for cost-conscious organizations.
IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.
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https://www.ibm.com/products/spss-modeler/pricing
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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 Features
KNIME has many valuable key features. Some of the most useful ones include:
KNIME Benefits
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.
An Emeritus Professor at a university says, “It can read many different file formats. It can very easily tidy up your data, deleting blank rows, and deleting rows where certain columns are missing. It allows you to make lots of changes internally, which you do using JavaScript to put in the conditional. It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured.”
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.”
We monitor all Data Mining 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.
