SAP Analytics Cloud: Predictive Analytics

. . . 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