SAP’s Predictive Analysis allows users to leverage many types of algorithms and visualizations. One of the interesting algorithms is Apriori also known as association analysis or basket analysis.

In this video I will demonstrate how to use the Apriori algorithms on data from the Titanic accident.

The business question: Watch this video if you would like some arguments to use with your boss for travelling 2nd or 1 first class.


As shown in this video there is just a few steps needed to perform this very powerful data mining analysis with SAP Predictive Analysis:

Lessons learned from the Apriori rules generated:

* Don’t travel 3rd class if you want to survive.

* Don’t be part of the crew if you want to survive.

* Certainly don’t be a male if you want to survive.

So to answer the business question. If you want a higher chance to survive travelling: travel 1 first class & be female.


With this step-by-step approach you will be able to enhance SAP Predictive Analysis with even further statistical algorithms and charts / visualizations.

Best regards,

Kurt Holst


Pre-requisites – installed software:

SAP Predictive Analysis version 1.0.11

R 2.15 with the necessary libraries with r algorithms.

R Titanic dataset is pre-installed with R.

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  1. Yasemin ULUTURK

    Very inspiring. Besides the fact of the lessons learnt (I won’t travel 3rd class, lucky of being female 😉 ) it gives an insight on how to use association rules. It is nice to see association rules being used except purchase behavior analysis.




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