SAP Predictive Analytics

SAP Predictive Analytics

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Score 9.0 out of 100
SAP Predictive Analytics


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What is SAP Predictive Analytics?

SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.

Entry-level set up fee?

  • No setup fee


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

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Features Scorecard

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Product Details

What is SAP Predictive Analytics?

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. The products offers predictive automation, allowing customers to unlock the potential of Big Data from virtually any source. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software aims to make it easier to make better, more profitable decisions across the enterprise.

SAP Predictive Analytics Features

  • Supported: Automate analytics with Python API
  • Supported: Publish predictive models to business applications
  • Supported: Support data privacy to achieve legal compliance

SAP Predictive Analytics Competitors

SAP Predictive Analytics Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.

IBM SPSS, Oracle Machine Learning, and SAS Advanced Analytics are common alternatives for SAP Predictive Analytics.

The most common users of SAP Predictive Analytics are from Small Businesses (1-50 employees) and the Computer Software industry.
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Reviews and Ratings




(1-3 of 3)
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Ali Kazempour | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • All different common database like JDBC, XLS, CSV, and more types can be connected
  • Easy integration with SAP Lumira workflow
  • Simple and conceptual design and convenient diagrams
  • Working with this software is very simple and enjoyable for me as [an] IT consultant and expert, but it is a bit complicated for novice users.
  • Some big data takes more time‌to load, which I think could be faster
Abdelhalim DADOUCHE | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • It doesn't require you to have a Ph.D. to build models!
  • You can use it to address a very large and wide dataset without worrying about sampling.
  • Automation is in the product DNA. You can prepare your data, ingest it into the "Kernel", then get insights about what was found, decide to publish it and schedule scoring tasks or model refresh in the same product.
  • The "User Experience" is sometimes lacking some clear basic things. Maybe a migration to a cloud-based environment will help bridge that gap.
  • API is probably the next item on my list. The existing one is not easy to access or use which limits the integration capabilities.
Josh Anderson | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
Review Source
  • Ability to use built-in algorithms or expand using R. This means that (with training) casual users can take advantage but also data analysts can do their thing!
  • Integration and consistency with Lumira. Even Lumira on its own has a quick 'predict' functionality (although limited/black box)
  • Ability to do the analysis and then present visually using the Lumira visualization capabilities
  • It's extremely hard to get started. We even have a data scientist who, when we put Predictive Analytics in front of them, they could not intuitively create a data model and start analyzing. Even with deep knowledge of data analysis, the interface isn't intuitive and it's hard to get to the point of having imported a data set and start analyzing/predicting
  • Our platform team had confusion installing Predictive Analytics, particularly on the BI Platform. Additional complexity came when it came to using APL Libraries (AFL Wrapper or Stored Procedures)
  • We are still working on merging datasets. In theory, we get how to do it but we come across all sorts of issues which don't occur in Spotfire (missing records etc.)
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