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IBM SPSS Modeler

IBM SPSS Modeler

Overview

What is IBM SPSS Modeler?

IBM SPSS Modeler is a 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 can use it for data preparation and discovery, predictive analytics,…

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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

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Pricing

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IBM SPSS Modeler Personal

4,670

On Premise
per year

IBM SPSS Modeler Professional

7,000

On Premise
per year

IBM SPSS Modeler Premium

11,600

On Premise
per year

Entry-level set up fee?

  • Setup fee optional
For the latest information on pricing, visithttps://www.ibm.com/us…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Starting price (does not include set up fee)

  • $499 per month
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Product Demos

CHAID Demo 1394186

YouTube

IBM SPSS Modeler Demo #4 Deploy Analysis Results

YouTube

IBM SPSS Modeler Demo #3 Analyze Data

YouTube

IBM SPSS Modeler: Data Processing (Data Manipulation)

YouTube
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Product Details

What is IBM SPSS Modeler?

IBM SPSS Modeler is a 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 can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.


Organizations use IBM SPSS Modeler to find answers to their critical business questions, such as:

  • Which customers are likely to churn?
  • What products and services are prospects likely to purchase together?
  • Which insurance claims have a high probability of fraud?
  • Which machines on the assembly line are likely to fail?
  • Where do we need to deploy additional law enforcement resources?
  • How can we select the right applicants for the right roles?

IBM SPSS Modeler is also available within IBM Cloud Pak for Data, a containerized data and AI platform used to build and run predictive models anywhere — on any cloud and on premises. IBM Cloud Pak for Data as a Service enables running Modeler flows on the public cloud.

IBM SPSS Modeler Features

  • Supported: Visual analysis streams
  • Supported: Broad range of advanced analytical techniques
  • Supported: Automatic data preparation

IBM SPSS Modeler Screenshots

Screenshot of 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.Screenshot of 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.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.

IBM SPSS Modeler Video

IBM SPSS Modeler Competitors

IBM SPSS Modeler Technical Details

Deployment TypesOn-premise
Operating SystemsWindows, Linux, Mac, AIX
Mobile ApplicationNo
Supported LanguagesEnglish, French, German, Italian, Spanish, Japanese, Simplified Chinese, Traditional Chinese, Brazilian Portuguese, Korean, Polish, Russian

Frequently Asked Questions

IBM SPSS Modeler is a 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 can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.

IBM SPSS Modeler starts at $499.

SAS Viya, RapidMiner, and KNIME Analytics Platform are common alternatives for IBM SPSS Modeler.

The most common users of IBM SPSS Modeler are from Enterprises (1,001+ employees).
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Comparisons

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Reviews From Top Reviewers

(1-5 of 7)

IBM SPSS Modeler a Statistical Tool for the New Researcher

Rating: 7 out of 10
September 02, 2024
GD
Vetted Review
Verified User
IBM SPSS Modeler
3 years of experience
  • Wide range of statistical techniques
  • Good tables and charts
  • Integrates with Excel
Cons
  • Appears slow with very large data sets
  • Lack of frequent updates
  • cost reduction

SPSS Modeler is a great addition to Data Science toolkit, faster results than coding

Rating: 10 out of 10
January 25, 2021
BH
Vetted Review
Verified User
IBM SPSS Modeler
4 years of experience
  • Fast code builder.
  • No need to maintain software versioning.
  • Visual code, easy to see what's happening.
Cons
  • Details of models and nodes requires some "digging", "clicking".
  • Customization of versions is hard to implement.
  • Latest open source code packages take time to integrate into the application.

IBM SPSS Modeler is My Choice

Rating: 10 out of 10
May 10, 2021
TD
Vetted Review
Verified User
IBM SPSS Modeler
16 years of experience
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
Cons
  • The graphics are weak.

Appreciation of Stats: Recommendation for Consumers and Producers

Rating: 10 out of 10
October 09, 2019
CP
Vetted Review
Verified User
IBM SPSS Modeler
17 years of experience
  • Inputting data
  • Test selection
  • Data manipulation
  • Providing sandbox data sets
  • Two week trial for students considering purchase
  • Reasonable rent prices
Cons
  • Including MCAR in basic packages
  • Standardise language across dialogue windows
  • Enable 'undo' after sorting cases
  • Include Bayesian options

A very good statistical analysis tool

Rating: 8 out of 10
May 16, 2019
  • A very nice and easy to use interface.
  • A great variety of analytics, from statistical calculation to data validation and predictive statistics.
  • Has a steep learning curve.
Cons
  • Has very old style graphs, with lots of limitations.
  • Some advanced statistical functions cannot be done through the menu.
  • The data connectivity is not that extensive.
  • It's an expensive tool.
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