New Text Analytics Add-on now available for Modeler Subscription.

New Text Analytics Add-on now available for Modeler Subscription.

Key Features

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 spatial AR in STP (spatiotemporal prediction). Generative adversarial networks (GANs) and reinforcement learning for deep learning.

SPSS Modeler demo 1: Access data

This first in a series of four tutorials on IBM SPSS® Modeler introduces the powerful capabilities of the tool, including:
• Accessing data
• Manipulating data
• Analyzing data
• Deploying the results of your analysis
Then, you’ll be taken on a deeper exploration of how you can use SPSS Modeler to access and merge a variety of data sources.

SPSS Modeler demo 2: Manipulate data

This second tutorial demonstrates how you can use SPSS Modeler to manipulate data in a stream and prepare it for analysis by cleaning and processing the date for presentation into an algorithm. And, SPSS Modeler makes it easier to modify rows and columns of information in your dataset to prepare it for analysis.

SPSS Modeler demo 3: Analyze data

This third tutorial demonstrates how you can use SPSS Modeler to analyze your data. SPSS Modeler offers a choice from a variety of pre-built algorithms to help you create models visually and intuitively. SPSS Modeler provides automated techniques that allow it to arrive at certain conclusions for you, thereby removing much of the guesswork.

SPSS Modeler demo 4: Deploy the results of your analysis

This fourth tutorial demonstrates how the SPSS Modeler can help you put the models you’ve developed and validated to use, yielding better decisions and improved business outcomes. And, SPSS Modeler offers code-free deployment, greatly simplifying the process of deploying your models into applications.

Customer Case Studies

Volvo

See how the Volvo Group used Modeler for predictive maintenance to fulfill uptime commitments.

Redcats Group

See how Redcats group was able to find new insights in their customer data to predict buying habits with SPSS Modeler.

O Boticario

See how O Boticario used SPSS Modeler to predict customer demand up to nine months in advance.

Next Steps

Try it now

Buy now and get started