An integrated family of software products
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IBM SPSSProduct Overview

  1. About IBM SPSS
  2. Pros of IBM SPSS
  3. Cons of IBM SPSS
  4. Breakdown of core features

IBM SPSS product overview

IBM SPSS is an integrated family of software products. It is a platform that enables users to build predictive models and execute analytics tasks. It helps business users of all skill levels to perform complex statistical analysis that can solve business and research problems quickly and efficiently.

IBM SPSS mainly consists of SPSS Statistics and SPSS Modeler. SPSS Statistics is a statistical software platform with a robust set of features to help users analyze data and understand large and complex datasets quickly. Organizations are able to extract actionable insights with a top-down hypothesis-testing approach.

SPSS Modeler is a graphical data science and predictive analytics platform. It is a visual drag-and-drop tool that helps speed up operational tasks to drive return-on-investment and accelerate time to value with a bottom-up hypothesis-generation approach. Organizations are able to go live in days, boost team productivity, start small, and scale according to security and governance requirements.

Pros of IBM SPSS

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  • User-friendly interface: IBM SPSS is easy to use, flexible, and accessible to users of all skill levels.
  • Advanced analysis tools: IBM SPSS offers advanced statistical analysis, text analysis, and a vast library of machine learning algorithms and models that are ready for immediate use.
  • Robust features: Open source extensibility, integration with big data, automation, and multiple deployment options are available.

Cons of IBM SPSS

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  • Interface update: Some users think that the software needs a fresher interface as well as improvement on default graphics.

Breakdown of core features

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Fast and powerful solution

IBM SPSS is designed to solve business and research problems with advanced algorithms, machine learning algorithms, procedures, and extensions that cover statistical and predictive analytics. It uses ad hoc analysis, hypothesis testing, geospatial analysis, predictive analytics, text analytics, and optimization to find new opportunities, improve efficiency, and minimize risk.

Open source extension

IBM SPSS allows users to enhance SPSS syntax with integration to R and Python code using a library of extensions or their own code.


Users can automate common tasks using SPSS syntax, using R and Python, or creating customized dialog boxes that use those languages. SPSS includes several types of coding and automation support such as scripting and CLEM.


IBM SPSS features and functionalities can be expanded with a multitude of available add-on modules such as additional builders and algorithms.

(Last updated on 02/02/2022 by Abby Dykes)

Quick Facts

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  • Basic/advanced statistical analysis and modeling
  • Machine learning algorithm libraries
  • Text analysis
  • Predictive analytics
  • Open source extension
  • Big data integration
  • Supports complete data science cycle
  • Graphs and charts
  • Easy-to-use GUI
  • Automation
  • Flexible deployment


  • IBM Data Science products
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  • Python
  • Esri
  • Zementis

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