Yesterday we released IBM SPSS Modeler 17.1 and IBM SPSS Analytic Server 2.1.  With this release we are extending the value of big data with new prediction and classification algorithms built to work at massive scale. This is a summary of the new features:

Modeler 17.1

  • Support for New SPSS Big Data Algorithms from Analytic Server
  • Custom Dialog Builder for Spark Python
    • Extend analysis with Python & run it at scale in Spark via Analytic Server
    • Expose Spark MLlib algorithms to Modeler users
  • Better performance for TM1 integration
  • Updated Platform Support
    • RHEL 7 & Canonical Ubuntu on Power Linux little endian
    • dashDB (SQL Pushback)
    • Amazon Redshift (SQL Pushback)

Analytic Server 2.1

  • New SPSS Big Data Algorithms
    • Random Trees
    • Linear Support Vector Machines
    • Generalized Linear Engine
    • Linear-AS
    • Tree-AS
  • Apache Spark integration
    • Improved performance & scalability
    • Access to Spark MLlib algorithms
  • Oen Data Platform alignment
    • BigInsights 4.1 & Hortonworks 2.3 support
    • Streamlined installation via Apache Ambari
  • Support for IBM Power Linux

spssSpark

3 comments on"New SPSS Modeler 17.1 and Analytic Server 2.1"

  1. Michelle Kelse December 02, 2015

    How do I get Spark to show up as an icon in SPSS Modeler 17.1?

  2. how to I get sql generation/optimization for redshift to work in modeler 17.1?

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