Preface

13

Target Audience

13

Book Structure

14

Acknowledgments

14

1 SAP’s Digital Business Framework

19

1.1 Digital Transformation

19

1.1.1 The Digital Transformation Imperative

19

1.1.2 What Does Digitalization Mean for Your Company?

21

1.1.3 SAP’s Role in Your Digital Transformation

23

1.2 SAP S/4HANA: The Digital Core

24

1.2.1 Business Needs for a Digital Core

24

1.2.2 The Evolution of ERP

25

1.2.3 Technologies

27

1.2.4 Key Principles

28

1.3 SAP S/4HANA Business Requirements

32

1.3.1 ERP in the Cloud (Software as a Service)

33

1.3.2 Real-Time Data via Prediction to Automation

35

1.3.3 Integrating the Digital Core

35

1.4 Summary

36

2 Analytics in the Digital Economy

37

2.1 Embedded Analytics versus Standalone Analytics

37

2.2 Combining Transactions and Analytics

41

2.2.1 On a Single Platform

42

2.2.2 Within the Business Process

43

2.2.3 Within a Single User Interface

45

2.3 Summary

47

3 Architecture

49

3.1 Architecture Overview

49

3.1.1 Stack Overview: Journey of Data from Tables to Tiles

51

3.1.2 Building Blocks

55

3.2 Virtual Data Models in Core Data Services

66

3.2.1 Core Data Services

66

3.2.2 Virtual Data Models

77

3.3 Authorization and Security

82

3.3.1 Authorizations

82

3.3.2 Roles in Frontend Server

85

3.4 SAP Fiori Programming Model: Access and Visualization

88

3.4.1 Service Enablement

90

3.4.2 Data Access Protocol

91

3.4.3 SAP Fiori Catalog and Navigation Targets

94

3.5 Summary

96

4 Analytics for the Business User

99

4.1 Operational Insight-to-Action Using the Analytical List Page

99

4.1.1 Typical Usage

100

4.1.2 Features and Personalization Options

103

4.2 KPI Reporting and Analysis Using SAP Smart Business KPIs

110

4.2.1 Typical Usage

111

4.2.2 Features and Personalization Options

114

4.3 Multidimensional Reporting

123

4.3.1 Typical Usage

123

4.3.2 Features and Personalization Options

125

4.4 SAP Fiori Overview Pages

135

4.4.1 Typical Usage

135

4.4.2 Features and Personalization Options

138

4.5 Analysis Path Framework

144

4.5.1 Typical Usage

144

4.5.2 Features and Personalization Options

147

4.6 Additional Functions

159

4.6.1 Query Browser

159

4.6.2 App Catalog

161

4.6.3 App Search

164

4.6.4 Notification Area

166

4.6.5 User Assistance

168

4.7 Summary

170

5 Predefined Analytics Content

173

5.1 Content Delivered with SAP S/4HANA

174

5.2 Analytics Content and SAP Best Practices

180

5.3 Line-of-Business-Specific Best Practices

189

5.3.1 Procurement Analytics Content

189

5.3.2 Financial Planning and Analysis Content

192

5.3.3 Manufacturing Analytics Content

196

5.4 Integration Best Practices

200

5.4.1 SAP BW Integration

200

5.4.2 SAP BusinessObjects BI Platform Integration

205

5.4.3 SAP Cloud Platform Integration

206

5.5 Summary

207

6 Analytics for the Analytics Specialist

209

6.1 The Analytics Specialist Role

209

6.1.1 Process Overview

210

6.1.2 Technical Details and Process Mapping

213

6.2 Browsing the Virtual Data Model

216

6.2.1 Overview

217

6.2.2 Features and Options

219

6.3 Creating and Publishing Data Sources and Queries

225

6.3.1 Custom CDS Views

226

6.3.2 Custom Analytical Queries

233

6.4 Maintaining SAP Smart Business KPIs

246

6.4.1 Process Overview

246

6.4.2 Creating a KPI

248

6.4.3 Creating an Evaluation

252

6.4.4 Creating an SAP Fiori Launchpad Tile and DrillDown

257

6.4.5 Configure Drilldown Application

260

6.4.6 Deploy KPI Tile

266

6.4.7 KPI Workspace

269

6.5 Maintaining Reports

273

6.5.1 Typical Usage and Examples

274

6.5.2 Customization Options

275

6.6 Analysis Path Framework

280

6.6.1 Process Overview

281

6.6.2 Modeling APF Configurations

283

6.7 Defining Date Functions

292

6.7.1 Defining Date Functions

292

6.7.2 Using Date Functions in the KPI Configuration

297

6.8 Creating SAP Fiori Launchpad Tiles for SAP Analytics Cloud Stories

299

6.9 Summary

302

7 Analytics for the IT Expert

303

7.1 The IT Expert Role

304

7.2 Creating and Consuming CDS Views

305

7.2.1 Exploring CDS Views

305

7.2.2 Consuming CDS Views with the Analytical Engine

315

7.2.3 Consuming CDS Views with OData Services

318

7.3 Summary

321

8 Additional Extensibility Options

323

8.1 Custom Business Objects

323

8.2 Custom Fields and Logic

331

8.3 Summary

340

9 Data Warehousing

343

9.1 Do You Need Additional Data Warehouses?

344

9.2 Data Management for SAP S/4HANA

347

9.2.1 Overview

347

9.2.2 SAP BW/4HANA

350

9.3 SAP SQL Data Warehousing with SAP HANA 2.0

364

9.4 Big Data Warehousing

367

9.4.1 Data Lakes

368

9.4.2 SAP Data Hub

368

9.5 Summary

369

10 Business Intelligence

371

10.1 Should You Use Additional Business Intelligence Solutions?

371

10.2 SAP Analytics Suite

372

10.2.1 Portfolio Structure

373

10.2.2 Platform and Architecture

375

10.2.3 SAP Lumira

376

10.2.4 SAP BusinessObjects Web Intelligence

378

10.2.5 SAP Analysis for Microsoft Office

379

10.2.6 Integration

380

10.3 SAP Analytics Cloud

381

10.3.1 Self-Service Business Intelligence

382

10.3.2 Hichert Standards Support

383

10.3.3 SAP Digital Boardroom

384

10.3.4 Integration

384

10.3.5 Planning

387

10.4 Summary

389

11 Predictive Analytics and Machine Learning

391

11.1 Process Overview

392

11.2 Machine Learning Solution Architecture

396

11.3 Machine Learning Use Cases for SAP S/4HANA

397

11.3.1 SAP Cash Application

397

11.3.2 Quantity Contract Consumption App

398

11.3.3 Project Cost Forecasting App

399

11.4 SAP S/4HANA Embedded Machine Learning

400

11.4.1 SAP Predictive Analytics Integrator

401

11.4.2 Using Embedded Machine Learning Applications

404

11.4.3 Creating a Predictive App with SAP Analytics Cloud and SAP S/4HANA Cloud

407

11.5 Summary

413

Appendices

415

A Future Outlook

415

A.1 New Environment for the Analytics Specialist

415

A.2 Data Extraction from SAP S/4HANA Cloud to SAP BW/4HANA

416

A.3 Additional Predictive Models Use Cases

417

A.4 Conversational UIs

418

A.5 Cross-Solution Analytics

418

B The Authors

421