Altair RapidMiner and WPS Analytics are products in the analytics category. Altair RapidMiner has an advantage with its feature-rich platform, while WPS Analytics stands out with its intuitive design and integration.
Features: Altair RapidMiner provides automated machine learning, robust data preprocessing, and extensive data visualization tools. WPS Analytics is known for comprehensive statistical analysis and seamless integration with open-source languages like R and Python, along with strong scripting support.
Ease of Deployment and Customer Service: WPS Analytics offers straightforward deployment with responsive customer service and quick installations. Altair RapidMiner, although more complex in deployment, provides excellent post-deployment support and thorough onboarding.
Pricing and ROI: Altair RapidMiner involves higher initial setup costs, justified by its capabilities for long-term ROI. WPS Analytics presents a more cost-effective setup with competitive pricing, offering strong value for budget-conscious businesses.
| Product | Market Share (%) |
|---|---|
| Altair RapidMiner | 5.0% |
| WPS Analytics | 0.6% |
| Other | 94.4% |
| Company Size | Count |
|---|---|
| Small Business | 12 |
| Midsize Enterprise | 5 |
| Large Enterprise | 8 |
Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.
RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.
What features make Altair RapidMiner stand out?Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.
WPS is used in production on a huge range of systems at sites around the world. Thousands of analysts are using WPS in their daily data processing and analysis tasks, and thousands more rely on the heavy-lifting ability of WPS overnight and scheduled processing to deliver the information they require. Customers are able to choose to run WPS software on IBM z/OS Mainframes, servers and workstations running UNIX, Linux, Solaris, AIX, macOS and the full range of Microsoft Windows operating systems to fit in with existing or planned infrastructure.
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.
