PAII10 SAP Predictive Analytics

Transcription

1 PAII10 SAP Predictive Analytics. COURSE OUTLINE Course Version: Course Duration: 5 Day(s)

2

3 SAP Copyrights and Trademarks 2017 SAP SE or an SAP affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. Please see for additional trademark information and notices. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP SE or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE s or its affiliated companies strategy and possible future developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions. Copyright. All rights reserved. iii

4 Typographic Conventions American English is the standard used in this handbook. The following typographic conventions are also used. This information is displayed in the instructor s presentation Demonstration Procedure Warning or Caution Hint Related or Additional Information Facilitated Discussion User interface control Example text Window title Example text iv Copyright. All rights reserved.

5 Contents vii Course Overview 1 Unit 1: Introduction to Predictive Analytics 1 Lesson: Introducing Predictive Analytics 1 Lesson: Understanding SAP Predictive Analytics 1 Lesson: Describing Use Cases 3 Unit 2: Foundations of SAP Automated Analytics 3 Lesson: Introducing SAP Automated Analytics 3 Lesson: Understanding Foundations 3 Lesson: Understanding Data Encoding 3 Lesson: Understanding Model Building 5 Unit 3: Classification Modeling with SAP Automated Analytics 5 Lesson: Understanding Classification Modeling with SAP Automated Analytics 5 Lesson: Understanding Classification Model Output 5 Lesson: Understanding the Confusion Matrix 5 Lesson: Applying a Model 5 Lesson: Improving Predictive Power and Prediction Confidence 5 Lesson: Reducing the Number of Variables 6 Lesson: Understanding Data Deviation Testing 6 Lesson: Describing Advanced Functionality 6 Lesson: Understanding Advanced Data Description Functionality 7 Unit 4: Regression Modeling with SAP Automated Analytics 7 Lesson: Understanding Regression Modeling with SAP Automated Analytics 9 Unit 5: Clustering with SAP Automated Analytics 9 Lesson: Introducing Cluster Analysis 9 Lesson: Understanding Options: Target Or No Target 9 Lesson: Understanding Cluster Range 9 Lesson: Understanding Model Debriefing 9 Lesson: Applying the Model 9 Lesson: Describing Segmented Models 11 Unit 6: Time Series with SAP Automated Analytics 11 Lesson: Describing Time Series with SAP Automated Analytics Copyright. All rights reserved. v

6 13 Unit 7: SAP Data Manager 13 Lesson: Introducing SAP Data Manager 13 Lesson: Understanding Data Manipulation 13 Lesson: Using SAP Data Manager 15 Unit 8: SAP Predictive Factory 15 Lesson: Introducing SAP Predictive Factory 15 Lesson: Completing Setup 15 Lesson: Importing Models 15 Lesson: Creating and Scheduling Tasks 15 Lesson: Understanding Segmented Modeling 17 Unit 9: Social and Recommendations Functionality 17 Lesson: Understanding the Social Functionality 17 Lesson: Understanding the Recommendations Functionality 19 Unit 10: SAP Predictive Analytics Expert 19 Lesson: Understanding SAP Predictive Analytics Expert 21 Unit 11: SAP Cloud Platform Predictive Services 21 Lesson: Describing SAP Cloud Platform Predictive Services vi Copyright. All rights reserved.

7 Course Overview TARGET AUDIENCE This course is intended for the following audiences: Application Consultant Technology Consultant Super / Key / Power User System Administrator Technology Consultant Copyright. All rights reserved. vii

8 viii Copyright. All rights reserved.

9 UNIT 1 Introduction to Predictive Analytics Lesson 1: Introducing Predictive Analytics Describe predictive analytics Lesson 2: Understanding SAP Predictive Analytics Describe SAP Predictive Analytics Lesson 3: Describing Use Cases Describe use cases Copyright. All rights reserved. 1

10 Unit 1: Introduction to Predictive Analytics 2 Copyright. All rights reserved.

11 UNIT 2 Foundations of SAP Automated Analytics Lesson 1: Introducing SAP Automated Analytics Explain SAP Automated Analytics Lesson 2: Understanding Foundations Explain data cutting strategy Lesson 3: Understanding Data Encoding Prepare data Lesson 4: Understanding Model Building Describe model building methodology for Automated Analytics Copyright. All rights reserved. 3

12 Unit 2: Foundations of SAP Automated Analytics 4 Copyright. All rights reserved.

13 UNIT 3 Classification Modeling with SAP Automated Analytics Lesson 1: Understanding Classification Modeling with SAP Automated Analytics Create a classification model Lesson 2: Understanding Classification Model Output Explain classification model output Lesson 3: Understanding the Confusion Matrix Explain the confusion matrix Lesson 4: Applying a Model Apply a model Lesson 5: Improving Predictive Power and Prediction Confidence Improve predictive power and prediction confidence Lesson 6: Reducing the Number of Variables Copyright. All rights reserved. 5

14 Unit 3: Classification Modeling with SAP Automated Analytics Reduce the number of variables Lesson 7: Understanding Data Deviation Testing Perform data deviation on data with target and without target Lesson 8: Describing Advanced Functionality Use gain chart and advanced functionality Lesson 9: Understanding Advanced Data Description Functionality Use composite variables and geolocation tiles 6 Copyright. All rights reserved.

15 UNIT 4 Regression Modeling with SAP Automated Analytics Lesson 1: Understanding Regression Modeling with SAP Automated Analytics Build a regression model Copyright. All rights reserved. 7

16 Unit 4: Regression Modeling with SAP Automated Analytics 8 Copyright. All rights reserved.

17 UNIT 5 Clustering with SAP Automated Analytics Lesson 1: Introducing Cluster Analysis Describe clustering and segmentation Lesson 2: Understanding Options: Target Or No Target Differentiate between supervised and unsupervised segmentation Lesson 3: Understanding Cluster Range Explain cluster range Lesson 4: Understanding Model Debriefing Understand cluster profiles Lesson 5: Applying the Model Apply segmentation model options Lesson 6: Describing Segmented Models Copyright. All rights reserved. 9

18 Unit 5: Clustering with SAP Automated Analytics Improve classification and regression models with segmentation 10 Copyright. All rights reserved.

19 UNIT 6 Time Series with SAP Automated Analytics Lesson 1: Describing Time Series with SAP Automated Analytics Train a time series Copyright. All rights reserved. 11

20 Unit 6: Time Series with SAP Automated Analytics 12 Copyright. All rights reserved.

21 UNIT 7 SAP Data Manager Lesson 1: Introducing SAP Data Manager Describe data preperation and SAP Data Manager Lesson 2: Understanding Data Manipulation Explain data manipulation functionality Lesson 3: Using SAP Data Manager Explain the Data Manager benefits and process Copyright. All rights reserved. 13

22 Unit 7: SAP Data Manager 14 Copyright. All rights reserved.

23 UNIT 8 SAP Predictive Factory Lesson 1: Introducing SAP Predictive Factory Explain Predictive Factory Lesson 2: Completing Setup Describe architecture and roles Lesson 3: Importing Models Import models Lesson 4: Creating and Scheduling Tasks Explain model scheduling functionality Lesson 5: Understanding Segmented Modeling Explain time series segmented model Copyright. All rights reserved. 15

24 Unit 8: SAP Predictive Factory 16 Copyright. All rights reserved.

25 UNIT 9 Social and Recommendations Functionality Lesson 1: Understanding the Social Functionality Build a Social model Lesson 2: Understanding the Recommendations Functionality Create a retail recommendation analysis Copyright. All rights reserved. 17

26 Unit 9: Social and Recommendations Functionality 18 Copyright. All rights reserved.

27 UNIT 10 SAP Predictive Analytics Expert Lesson 1: Understanding SAP Predictive Analytics Expert Describe SAP Predictive Analytics Expert and Predictive Analysis Library (PAL) Copyright. All rights reserved. 19

28 Unit 10: SAP Predictive Analytics Expert 20 Copyright. All rights reserved.

29 UNIT 11 SAP Cloud Platform Predictive Services Lesson 1: Describing SAP Cloud Platform Predictive Services Use Data Manager on a large data set, build an Analytic Data Set (ADS), build a classification model, and productionize it in Predictive Factory Copyright. All rights reserved. 21