Build predictive models and score transactional data in real time
IBM® SPSS® Modeler is a powerful, versatile data mining workbench that enables organizations to build accurate predictive models and then rapidly deploy them, all without programming.
IBM SPSS Modeler for Linux on System z merges the predictive power of SPSS Modeler with the performance, security and scalability of the System z platform. This combination enables organizations to extract insights from their high-volume transactional applications running on DB2 for z/OS, and use those insights to make smart, proactive decisions. With SPSS Modeler for Linux on System z, businesses can create models and score new transactional data in real time, reducing the cost and complexity of operational decision-making.
SPSS Modeler for Linux on System z has features to help you:
- Easily access and integrate data from a variety of sources and prepare it for analysis.
- Rapidly build and validate models using advanced techniques and algorithms.
- Perform data mining and text analysis within an interactive, visual environment.
- Automate the execution of models and deploy results into existing systems and processes.
- Integrate with transactional applications running on IBM DB2® for z/OS to improve the accuracy, speed and performance of real-time scoring while reducing cost and complexity.
IBM SPSS Modeler for Linux on System z Screenshots
Easily access, manage and integrate data
- Access operational data from Cognos Business Intelligence, IBM DB2®, Oracle, Microsoft SQL Server, IBM Informix®, IBM Netezza, mySQL (Oracle), and Teradata, as well as mainframe data through DB2 for z/OS and IBM Classic Federation Server support.
- Combine and resolve like entities, even when the entities do not share any key values.
- Choose from the multiple data-cleaning options: remove or replace invalid data, automatically impute missing values and mitigate outliers and extremes.
- Apply automatic data preparation to get data ready for analysis in a single step.
Rapidly build and validate models
- Perform a variety of modeling approaches in a single run and compare the results of the different methods.
- Select which models to use in deployment without having to run them all individually and then compare performance.
- Use an array of advanced data mining techniques to meet the needs of any application, including classification, segmentation, association, time-series and forecasting algorithms.
- Choose from three automated modeling methods: Auto Classifier, Auto Numeric and Auto Cluster.
- Fine-tune selected models based on statistical confidence levels.
Perform data mining and text analysis
- Visualize every step of the data mining process as part of an interactive "stream." Streams help analysts and business users collaborate by adding business knowledge and domain expertise to the data mining process.
- Unlock concepts trapped in unstructured data, such as web activity, blog content, customer feedback, emails and social media content, then combine with structured data to improve model accuracy.
- Transform information about relationships into key performance indicators that show the social behavior of individuals and groups.
- Create interactive graphs to help you explore and display text data and patterns for instant analysis.
- Apply powerful classification and categorization techniques that transform text into an analytical asset.
Automate model execution and deploy results
- Enable many analysts to work simultaneously without straining computing resources.
- Support in-database mining and efficiently processes large amounts of data.
- Extend the benefits of predictive analytics across geographic or functional lines and put results in the hands of decision makers quickly.
- Export data to databases, IBM Cognos Business Intelligence packages, SPSS Statistics, SPSS Data Collection, delimited text files, Excel, SAS or HTML.
- Excel, SAS, or XML Manage analytical assets and automate analytical processes by using SPSS Modeler Premium with IBM SPSS Collaboration and Deployment Services.
Integrate with transactional applications running on IBM DB2® for z/OS
- Score data within the database and in real time against transactional data such as high volume sales, customer service and claims transactions, increasing the timeliness of the score and making it available to more end users.
- Score new and relevant data directly in online transaction processing (OLTP) applications.
- Scale SPSS Modeler to larger data volumes to improve the accuracy of the data models and patterns created.
- Provide the performance needed to meet and exceed the service level agreements (SLAs) of the OLTP applications or departments.