Available plans:
IBM SPSS Modeler 30-Day Trial with Add-ons
Modernize data science – from data discovery to machine learning and application development.
Show details Hide details - Powerful – Accelerate time to value with data science lifecycle management. Out-of-the-box, industry-leading algorithms and capabilities including machine learning / deep learning, text analytics and geospatial analysis.
- Versatile – Optimize productivity of analysts and data scientists. Guides users with an intuitive, graphical interface. Extends to open source technologies. Coding optional.
- Scalable – Grow with your business, from desktop to deployment and optimization. Designed for mission-critical, hybrid cloud implementation.
- Flexible – Choose the licensing option that best fits your needs: desktop, monthly subscription or enterprise perpetual license.
IBM SPSS Modeler Base Edition
IBM SPSS Modeler: The power of predictive intelligence
Show details Hide details - Data access and export without data size limits
- Automatic data prep, wrangling, ETL, ad-hoc queries
- 40+ base machine learning algorithms, auto-modeling
- R & Python extensibility, Python scripting
- Geospatial analytics
- Python algorithms natively available without code, including XGBoost
- Integration with Decision Optimization
The following add-ons are available for your base product subscription:
- SQL Optimization Add-on (included in trial)
- Adds ability to push back the processing of many common data processing steps to relational databases and Hadoop.
- Text Analytics Add-on (included in trial)
- Adds ability to use linguistic technologies and natural language processing to process a unstructured text data in documents.
IBM SPSS Modeler Subscription delivers a comprehensive predictive analytics platform, designed to bring predictive intelligence to everyday business problems, enabling front-line employees or systems to make more effective decisions and improve outcomes. Modeler scales from desktop installations through to larger deployments that are integrated within operational systems and provides a range of advanced analytics including text analytics, entity analytics, social network analysis, automated modeling and data preparation in addition to decision management and optimization. This enables organizations to improve business processes and help people or systems consistently make the right decisions by delivering recommended actions at the point of impact.
- Support for many data sources
- Modeler can read data from flat files, spreadsheets, major relational databases, IBM Planning Analytics and Hadoop. Extend Modeler's capabilities to push back data processing with the SQL Optimization add-on (subscription) or the Analytic Server (perpetual licenses).
- Visual analysis streams
- Use an intuitive graphical interface to visualize each step in the data mining process as part of a stream. Analysts and business users can easily add expertise and business knowledge to the process.
- Automatic data preparation
- Transform data automatically into the best format for the most accurate predictive models. Analyze data, identify fixes, screen out fields and derive new attributes with just a few clicks.
- Automated modeling
- Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.
- A range of algorithmic methods
- Choose from multiple machine learning techniques, including classification, segmentation and association algorithms including out of the box algorithms leveraging Python and Spark. Use languages such as R and Python to extend modeling capabilities.
- Text analytics
- Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in blog content, customer feedback, emails and social media comments.
- Geospatial analytics
- Explore geographic data such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.
- Support for open source technologies
- Use R, Python, Spark and Hadoop to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you maintain control.
- Multiple deployment methods
- Using Modeler Gold, data scientists can schedule jobs to run at desired times. IT administrators can integrate deployment into existing systems for batch, real-time or streaming (through IBM Streams). Customers can deploy SPSS Modeler programs in the cloud through the Watson Machine Learning Bluemix service.
- Machine learning methods and algorithms
- Supports decision tree, neural networks and regression models. ARMA, ARIMA and exponential smoothing; transfer function with predictors and outlier detection; ensemble and hierarchical models; support vector machine (SVM) and temporal causal modeling (TCM); time series and spatialS AR in STP (spatiotemporal prediction). Generative adversarial networks (GANs) and reinforcement learning for deep learning.
