With SPSS Modeler flows, you can quickly develop predictive models using business expertise and deploy them into business operations to improve decision making. Designed around the long-established SPSS Modeler client software and the industry-standard CRISP-DM model it uses, the flows interface supports the entire data mining process, from data to better business results.

SPSS Modeler offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics. The methods available on the node palette allow you to derive new information from your data and to develop predictive models. Each method has certain strengths and is best suited for particular types of problems.

Data format

Relational: Tables in relational data sources

Tabular: .xls, .xlsx, .csv, .sav, .json, .xml, or .sas. For Excel files, only the first sheet is read.

Textual: In the supported relational tables or files

Data size

Any

How can I prepare data?

Use automatic data preparation functions

Write SQL statements to manipulate data

Cleanse, shape, sample, sort, and derive data

How can I analyze data?

Visualize data with many chart options

Identify the natural language of a text field

How can I build models?

Build predictive models

Choose from over 40 modeling algorithms, and many other nodes

Use automatic modeling functions

Model time series or geospatial data

Classify textual data

Identify relationships between the concepts in textual data

Getting started

To create an SPSS Modeler flow from the project's Assets tab, click New task > Build models as a visual flow.