Preface . 15 . Objective of This Book . 15 . Target Audience . 16 . Structure of This Book . 16 .

Acknowledgments . 18 . Conclusion . 19 I . Getting Started . 21 1 . An Introduction to Predictive Analytics in SAP Analytics Cloud . 23 1.

1 . The Importance of Predictive Analytics . 23 1.2 . Predictive Analytics in SAP Analytics Cloud . 26 1.3 . Customer Use Cases .

30 1.4 . Summary . 34 2 . What Are Predictive Scenarios? . 35 2.1 . Introducing Predictive Scenarios .

35 2.2 . The Different Types of Predictive Scenarios . 41 2.3 . The Predictive Ecosystem . 42 2.4 .

Summary . 51 3 . Predictive Analytics Projects . 53 3.1 . Predictive Analytics Project Stakeholders . 53 3.2 .

How to Implement a Predictive Analytics Project . 56 3.3 . Summary . 68 II . Time Series Forecasting Models . 69 4 . Introducing Time Series Forecasting Models .

71 4.1 . What Is Time Series Forecasting? . 71 4.2 . Data Sources for Time Series Forecasting Models . 76 4.3 .

End-to-End Time Series Forecasting Workflows . 82 4.4 . Summary . 84 5 . Using Predictive Forecasts in the Planning Process . 85 5.1 .

Business Scenario . 85 5.2 . Planning Models . 86 5.3 . Creating Time Series Forecasting Models with Predictive Planning . 92 5.

4 . Understanding Time Series Forecasting Models . 108 5.5 . Improving Time Series Forecasting Models with Predictive Planning . 120 5.6 . Saving Predictive Forecasts .

124 5.7 . Including Predictive Forecasts in a Story . 126 5.8 . Summary . 132 6 . Automating the Production of Predictive Forecasts .

133 6.1 . Introducing Multi Actions . 133 6.2 . Creating Predictive Steps in Multi Actions . 134 6.3 .

Using Multi Actions . 138 6.4 . Summary . 142 7 . Time Series Forecasting Models Using Datasets . 143 7.1 .

Business Scenario . 143 7.2 . Creating and Editing Datasets . 144 7.3 . Creating Time Series Forecasting Models on Datasets . 147 7.

4 . Understanding Time Series Forecasting Models Based on Datasets . 154 7.5 . Improving Time Series Forecasting Models Based on Datasets . 157 7.6 . Saving Predictive Forecasts .

158 7.7 . Including Predictive Forecasts in a Story . 160 7.8 . Summary . 167 8 . Best Practices and Tips for Time Series Forecasting Models .

169 8.1 . Going Beyond 1,000 Entities . 169 8.2 . Handling Time Series with Missing Data . 173 8.3 .

Considering Time Granularities . 177 8.4 . Creating Ad Hoc Performance Indicators . 180 8.5 . Generating What-If Simulations . 182 8.

6 . Forecasting Data at the Right Level . 184 8.7 . Summary . 186 9 . The Data Science behind Time Series Forecasting Models . 187 9.

1 . End-to-End Process . 187 9.2 . Additive Modeling Technique . 188 9.3 . Exponential Smoothing .

194 9.4 . Predictive Model Selection . 199 9.5 . Summary . 200 III . Classification Models and Regression Models .

201 10 . Introducing Classification Models and Regression Models . 203 10.1 . What Is Classification? . 203 10.2 . What Is Regression? .

207 10.3 . Data Sources for Classification Models and Regression Models . 209 10.4 . End-to-End Workflow . 213 10.5 .

Summary . 214 11 . Creating Classification Insights to Enrich Stories . 217 11.1 . Business Scenario . 217 11.2 .

Using Datasets with Classification Models . 218 11.3 . Creating Classification Models . 222 11.4 . Understanding Classification Models . 228 11.

5 . Improving Classification Models . 245 11.6 . Applying Classification Models . 248 11.7 . Enriching Stories with Classification Insights .

251 11.8 . Summary . 260 12 . Creating Regression Insights to Enrich Stories . 261 12.1 . Business Scenario .

261 12.2 . Using Datasets with Regression Models . 262 12.3 . Creating Regression Models . 266 12.4 .

Understanding Regression Models . 270 12.5 . Improving Regression Models . 275 12.6 . Applying Regression Models . 276 12.

7 . Enriching Stories with Regression Insights . 279 12.8 . Summary . 285 13 . The Data Science behind Classification Models and Regression Models . 287 13.

1 . Fitting a Predictive Function . 287 13.2 . Prerequisites to Generating a Model . 290 13.3 . Evaluating the Model Performance .

291 13.4 . End-to-End Automated Modeling . 297 13.5 . Generating Predictive Insights . 302 13.6 .

Summary . 305 14 . Conclusion . 307 14.1 . Lessons Learned . 307 14.2 .

The Future of Predictive Scenarios in SAP Analytics Cloud . 307 14.3 . Your Next Steps . 308 . The Authors . 309 . Index .

311.