Leverage IBM SPSS Modeler, the leading predictive analytics platform to identify trends, make predictions, and take action with machine learning.

IBM SPSS Statistics

IBM SPSS Modeler

Discover patterns in historical data to predict future events, make better decisions and achieve better outcomes with predictive analytics tools and machine learning.

Take advantage of a complete predictive analytics platform

As an authorized reseller and certified IBM Business Partner, Beyond the Arc can provide IBM SPSS Modeler software, training, and hands-on consulting.

What is IBM SPSS Modeler?

IBM SPSS Modeler is a powerful data mining and predictive analytics tool that helps organizations make more informed decisions. It enables users to quickly and easily analyze large amounts of data and use the insights they uncover to make more informed decisions. Modeler provides users with powerful visualizations, predictive analytics, and data mining capabilities. It also allows users to create models that can be used to identify trends and correlations in data, as well as to make predictions about future outcomes. By leveraging these capabilities, organizations can make more informed decisions, improve operational processes, and gain a competitive edge.

Get started quickly with IBM SPSS Modeler visual analysis streams:

With IBM SPSS Modeler, use an intuitive graphical interface to visualize each step of the AI development process as part of a modeler stream.

Analysts and business users can easily collaborate with data scientists add expertise and business knowledge to the machine learning process.  All in a powerful predictive analytics platform that brings predictive intelligence and machine learning to decisions with a range of advanced algorithms and techniques.

IBM SPSS Modeler - predictive analytics, machine learning, AI

Gain insights across your data, including unstructured text data:

Discover insights and solve problems faster by analyzing structured and unstructured data. IBM SPSS Modeler enables you to use natural language processing (NLP) and include text features into machine learning models. Access varied data from flat files, databases and big data environments such as Hadoop and Spark.

Choose from a range of methods in building machine learning models:

Choose from multiple machine learning techniques, including classification, segmentation and association algorithms. Use scripting languages such as R, Python and Spark to extend modeling capabilities.

Choose your deployment for machine learning and predictive analytics:

Choose from on-premises, cloud and hybrid deployment options to deliver predictive models through embedded services, business intelligence integration or simple reporting. IBM SPSS Modeler is now available as part of IBM Watson Studio. IBM Watson® Studio empowers you to operationalize AI and optimize decisions anywhere on IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, automate AI and machine learning lifecycles and speed time to value on an open multicloud architecture. Using IBM SPSS® Collaboration and Deployment Services, data scientists can schedule jobs to run at desired times. IT administrators can integrate deployment into existing systems for batch, real-time or streaming.

In Database Processing:

One key advantage of IBM SPSS Modeler is SQL Pushback. With SQL Pushback, you can push processing inside databases for enhanced performance, and in-database modeling is available for a variety of database platforms.

Prepare data automatically with easy-to-use predictive analytics tools:

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 in IBM SPSS Modeler.

Download the IBM SPSS Modeler datasheet for more info on features

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Key Features of IBM SPSS Modeler for Predictive Analytics, Machine Learning, and AI

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.

Want to select your own algorithms for machine learning? Choose from neural networks, random forests, decision trees, K-means clustering, logistic regression, and dozens of other options.

Automated Machine Learning and AI modeling with IBM SPSS Modeler predictive analytics

Automated ML and AI modeling with IBM SPSS Modeler

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. Check out the SPSS GitHub repo for examples on working with ArcGIS and Esri data with IBM’s predictive analytics tools.

Include geospatial factors in your predictive analytics

Support for R, Python, and other open source technologies

Use R, Python, Spark, Hadoop and other open source technologies to create machine learning and AI solutions to solve your organization’s toughest business challenges. Extend and complement these technologies for more advanced predictive analytics while you keep control.

Use open source machine learning and predictive analytics with IBM SPSS Modeler

Use open source predictive analytics and machine learning with IBM SPSS Modeler

Text analytics and natural language processing (NLP)

A cornerstone of AI is NLP and the ability to work with unstructured text. Capture key concepts, themes, sentiment and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails, and social media comments. This AI workbench allows you to do deep text mining and then easily visualize and share the results. Modeler works with a range of data formats including: databases, html, pdf, csv, Excel, Word, flat files, and more.