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 Business Hub are two analytics platforms that compete in the data science field. KNIME Business Hub holds the upper hand due to its flexibility, open-source nature, and lower cost, making it a preferred choice for many users.
Features: IBM SPSS Modeler is known for its advanced statistical tools, seamless integration with IBM analytics tools, and a wide range of algorithms for predictive modeling. KNIME Business Hub offers flexibility, an open-source platform, and the ease of integrating various data sources and tools, providing a customizable user experience.
Room for Improvement: IBM SPSS Modeler could improve its visual modeling capabilities and reduce complexity in data governance features. Additional enhancements in integration with non-IBM tools would be beneficial. KNIME Business Hub may require improvements in community-driven support, more intuitive user interfaces, and better handling of extremely large datasets to enhance efficiency.
Ease of Deployment and Customer Service: IBM SPSS Modeler provides robust customer support and a structured deployment process that benefits organizations integrated into the IBM ecosystem. In contrast, KNIME Business Hub offers a flexible deployment model appreciated for its adaptability in various technological environments, leveraging community-driven support and resources.
Pricing and ROI: IBM SPSS Modeler has a significant initial setup cost but delivers high ROI through its powerful analytics capabilities. In contrast, KNIME Business Hub, being open-source, reduces initial costs and offers high ROI by enabling extensive customization and adaptation to specific needs.
| Product | Market Share (%) |
|---|---|
| KNIME Business Hub | 14.6% |
| IBM SPSS Modeler | 20.2% |
| Other | 65.2% |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 32 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 16 |
| Large Enterprise | 29 |
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.
Buy
https://www.ibm.com/products/spss-modeler/pricing
Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947
KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.
KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.
What are the most important features of KNIME Business Hub?KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.
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.
