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What’s new for predictive in SAP HANA SPS 10?


SAP HANA SPS 10 was released today.

If you want to delve deeper and see working examples of what’s new in predictive then this blog can serve as your starting point.

The SAP HANA Academy produce hands-on video tutorials covering all aspects of SAP HANA and we have content covering SPS 10 from Day 1!

Here’s the main playlist: Predictive Analytics – What’s New SPS 10

The aim, as with previous SAP HANA support package stacks, is to publish a tutorial for each and every new SAP HANA predictive analysis library (PAL) algorithm as well as covering key enhancements to existing algorithms!

Here are direct links to all of the new PAL videos currently published that feature SPS 10:

Getting Started

PAL: 84. Getting Started with the Predictive Analysis Library

PAL: 91. Exception Handling

Data Preparation

PAL: 92. Data Preparation – Binning

PAL: 93. Data Preparation – Partitioning

Time Series

PAL: 85. Time Series – White Noise Test

PAL: 86. Time Series – Trend Test

PAL: 87. Time Series – Seasonality Test

PAL: 94. Time Series – Single and Double Exponential Smoothing

PAL: 95. Time Series – Seasonal ARIMA Model


PAL: 88. Statistics – Grubbs’ Test


PAL: 89. Classification – Parameter Selection and Model Evaluation (PSME)

PAL: 97. Classification – Confusion Matrix


PAL: 90. Clustering – Latent Dirichlet Allocation (LDA) for Text Mining

PAL: 96. Clustering – Gaussian Mixture Model

Each tutorial is accompanied by the SQL script shown and you can also download the example data in order to try the algorithms out for yourself. You’ll find the github link in the playlist description or go there directly via: saphanaacademy/PAL

Here’s the full academy playlist for the PAL: Predictive Analysis Library

Watch this space as there will be more videos added in the coming days…

UPDATE: June 26th: videos 91-95 added covering exception handling, accessing PAL via SQL window functions, and seasonal ARIMA modeling.

UPDATE: June 29th: videos 96-97 added covering Gaussian mixture model and confusion matrix.

As always feedback is most welcome – in the YouTube comments section, below, tweet me @pmugglestone or


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