Drive ROI and accelerate time to value with an intuitive, drag-and-drop data science tool
Overview
From drag-and-drop data exploration to machine learning
IBM SPSS Modeler is a leading visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations worldwide use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.
Features
Key Features for Modern Data Science
IBM SPSS Modeler automatically transforms data into optimal formats for accurate predictive modeling. Analyze datasets in just a few clicks, identify data issues, filter irrelevant fields, and create new attributes to accelerate preparation and improve model quality and speed.
Save and deploy models from leading machine learning frameworks such as Scikit-learn and TensorFlow alongside IBM SPSS Modeler. Seamlessly integrate models into your workflows, enabling faster deployment, greater flexibility, and consistent performance across diverse analytics environments.
Leverage IBM SPSS Modeler’s powerful graphics engine to visualize data and insights with clarity. Create compelling charts and visualizations that make complex patterns easy to understand, helping stakeholders quickly interpret results and act with confidence.
IBM SPSS Modeler automatically prepares and transforms data into optimal formats for predictive modeling. By streamlining data preparation, it reduces manual effort, improves accuracy, and helps you build high-quality models faster while ensuring consistent, reliable analytical outcomes.
IBM SPSS Modeler supports a wide range of advanced algorithms, including decision trees, neural networks, and regression models. These capabilities enable you to build highly accurate predictive models, uncover hidden patterns, and generate actionable insights across diverse data sets and business scenarios.
IBM SPSS Modeler integrates with R, Python, Spark, and Hadoop to extend analytics capabilities and scale performance. Leverage open-source tools and big data platforms to enhance modeling flexibility, process large datasets efficiently, and drive deeper, more impactful insights
Use cases
Drive Value with Predictive Analytics
Explore how IBM SPSS Modeler helps transform data into actionable insights across key business scenarios. From forecasting demand and detecting anomalies to improving customer engagement and clinical outcomes, it enables faster, smarter decisions at scale.
Case studies
Banca Alpi Marittime Credito Cooperativo Carrù S.c.p.A.
To accelerate credit requests, Banca Alpi Marittime joined with IBM Business Partner Analytics Network S.r.l. to launch Credit Scorecard App, an AI-powered approval engine backed by IBM® SPSS® Modeler technology. Using advanced data modeling, the system evaluates applicants’ financial information, authorizing credit lines without human intervention.
50%
of credit requests vetted and approved without human intervention
Integrations
Partner solution
data.world
Leverages the new data.world extension with IBM SPSS Modeler for exporting data sets between data.world and IBM SPSS Modeler.
Resources
Get started with SPSS Modeler
Explore the full SPSS portfolio to see how integrated analytics tools can expand your capabilities.
Pricing
SPSS Modeler pricing
Increase ROI and speed up time to value using an intuitive drag‑and‑drop data science tool built for faster model development and deployment. Discover simple, customizable pricing plans below.