SAP Predictive Analytics
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... Preface ... 17
... Objective ... 17
... Target Audience ... 18
... Structure of This Book ... 19
I ... Getting Started ... 21
1 ... An Introduction to Predictive Analytics ... 23
1.1 ... The Importance of Predictive Analysis ... 24
1.2 ... Predictive Analysis: Prescriptive and Exploratory ... 26
1.3 ... Preparing for a Successful Predictive Analysis Project ... 32
1.4 ... Industry Use Cases ... 37
1.5 ... Summary ... 39
2 ... What Is SAP Predictive Analytics? ... 41
2.1 ... Building Predictive Models with SAP Predictive Analytics ... 41
2.2 ... Automated Analytics and Expert Analytics ... 42
2.3 ... Mass Production of Predictive Models with the Predictive Factory ... 43
2.4 ... Data Preparation ... 45
2.5 ... Additional SAP Predictive Analytics Capabilities ... 47
2.6 ... Summary ... 48
3 ... Installing SAP Predictive Analytics ... 49
3.1 ... Recommended Deployments ... 50
3.2 ... Installing the SAP Predictive Analytics Server ... 51
3.3 ... Installing the SAP Predictive Analytics Client ... 57
3.4 ... Installing the Predictive Factory ... 61
3.5 ... Installing SAP Predictive Analytics Desktop ... 71
3.6 ... SAP HANA Installation Steps ... 74
3.7 ... Summary ... 75
4 ... Planning a Predictive Analytics Project ... 77
4.1 ... Introduction to the CRISP-DM Methodology ... 78
4.2 ... Running a Project ... 81
4.3 ... Summary ... 100
II ... The Predictive Factory ... 101
5 ... Predictive Factory ... 103
5.1 ... Predictive Factory: End-to-End Modeling ... 103
5.2 ... Creating a Project ... 105
5.3 ... External Executables ... 107
5.4 ... Variable Statistics ... 110
5.5 ... Summary ... 110
6 ... Automated Predictive Classification Models ... 111
6.1 ... Introducing Classification Models ... 112
6.2 ... Creating an Automated Classification Model ... 115
6.3 ... Understanding and Improving an Automated Classification Model ... 123
6.4 ... Applying an Automated Classification Model ... 139
6.5 ... The Data Science behind Automated Predictive Classification Models ... 149
6.6 ... Summary ... 172
7 ... Automated Predictive Regression Models ... 173
7.1 ... Introducing Regression Models ... 173
7.2 ... Creating an Automated Regression Model ... 174
7.3 ... Understanding and Improving an Automated Regression Model ... 179
7.4 ... Applying an Automated Regression Model ... 184
7.5 ... Summary ... 191
8 ... Automated Predictive Time Series Forecasting Models ... 193
8.1 ... Creating and Understanding Time Series Forecast Models ... 194
8.2 ... Mass Producing Time Series Forecasts ... 214
8.3 ... Productizing the Forecast Model ... 221
8.4 ... The Data Science behind Automated Time Series Forecasting Models ... 227
8.5 ... Summary ... 231
9 ... Massive Predictive Analytics ... 233
9.1 ... Deploying Predictive Models in Batch Mode ... 234
9.2 ... Model Quality and Deviation ... 241
9.3 ... Automatically Retraining Models ... 244
9.4 ... Scheduling and Combining Massive Tasks ... 250
9.5 ... Deploying Expert Analytics Models ... 253
9.6 ... Summary ... 256
III ... Automated Analytics ... 257
10 ... Automated Analytics User Interface ... 259
10.1 ... When to Use Automated Analytics ... 259
10.2 ... Navigating the User Interface ... 260
10.3 ... Exploring the Automated Analytics Modules ... 264
10.4 ... Summary ... 269
11 ... Automated Predictive Clustering Models ... 271
11.1 ... The Clustering Approach of Automated Analytics ... 272
11.2 ... Creating a Clustering Model ... 273
11.3 ... Supervised and Unsupervised Clustering ... 297
11.4 ... The Data Science behind Automated Clustering Models ... 299
11.5 ... Summary ... 300
12 ... Social Network Analysis ... 301
12.1 ... Terminology of Social Network Analysis ... 302
12.2 ... Automated Functionalities of Social Network Analysis ... 303
12.3 ... Creating a Social
Autor: | |
Nakladatel: | Rheinwerk Verlag |
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