SAP S/4HANA Embedded Analytics

See how SAP S/4HANA will change your BI processes! Explore the embedded analytics architecture and data model to learn how to perform analytics on live transactional data. Business user? Walk step-by-step through SAP Smart Business KPIs and multidimensional reporting. Analytics specialist? Master the virtual data model and creating KPIs. Jack of all trades? Create CDS views, apply custom fields and logic, or see what's coming up with machine learning. This is your complete guide to SAP S/4HANA embedded analytics!

Highlights include:
Architecture
Virtual data model (VDM)
SAP Fiori apps
SAP Smart Business
Key performance indicators (KPIs)
Operational reporting
CDS views
Customization
Data warehousing
Integration

Integrate with other SAP tools for data warehousing, business intelligence, and predictive analytics

Auteur
Anirban Kundu is a program director for SAP S/4HANA embedded analytics enablement at SAP. He has more than 17 years of experience across multiple roles including product management, corporate strategy, and consulting. Currently he is on a special assignment as a solution architect for operational analytics at Nestle. He has conducted more than 30 workshops about SAP S/4HANA embedded analytics for customers and partners across the US, EMEA and APJ. He has been a passionate advocate of enterprise analytics and has more than 14 years of experience building analytical application across range of technology and application areas. Previously, he worked as the global analytics lead for the SCM, PLM and manufacturing analytics and was instrumental in key product launches enhancing the SAP Analytics portfolio. He managed a consulting practice within the manufacturing driving strategy, growth and P&L for strategic insights. He received his MBA from IIM Bangalore and his B.Tech. in chemical engineering from IIT Bombay. He has also completed an immersion program at KAIST Business School, Seoul, South Korea.

Contenu
... Preface ... 13

... Target Audience ... 13

... Book Structure ... 14

... Acknowledgments ... 14

PART I ... Getting Started ... 17

1 ... SAP's Digital Business Framework ... 19

1.1 ... Digital Transformation ... 19

1.2 ... SAP S/4HANA: The Digital Core ... 24

1.3 ... SAP S/4HANA Business Requirements ... 32

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

2.3 ... Summary ... 47

3 ... Architecture ... 49

3.1 ... Architecture Overview ... 49

3.2 ... Virtual Data Models in Core Data Services ... 66

3.3 ... Authorization and Security ... 82

3.4 ... SAP Fiori Programming Model: Access and Visualization ... 88

3.5 ... Summary ... 96

PART II ... Analytics by User Type ... 97

4 ... Analytics for the Business User ... 99

4.1 ... Operational Insight-to-Action Using the Analytical List Page ... 99

4.2 ... KPI Reporting and Analysis Using SAP Smart Business KPIs ... 110

4.3 ... Multidimensional Reporting ... 123

4.4 ... SAP Fiori Overview Pages ... 135

4.5 ... Analysis Path Framework ... 144

4.6 ... Additional Functions ... 159

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

5.4 ... Integration Best Practices ... 200

5.5 ... Summary ... 207

6 ... Analytics for the Analytics Specialist ... 209

6.1 ... The Analytics Specialist Role ... 209

6.2 ... Browsing the Virtual Data Model ... 216

6.3 ... Creating and Publishing Data Sources and Queries ... 225

6.4 ... Maintaining SAP Smart Business KPIs ... 246

6.5 ... Maintaining Reports ... 273

6.6 ... Analysis Path Framework ... 280

6.7 ... Defining Date Functions ... 292

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

7.3 ... Summary ... 321

8 ... Additional Extensibility Options ... 323

8.1 ... Custom Business Objects ... 323

8.2 ... Custom Fields and Logic ... 331

8.3 ... Summary ... 340

PART III ... Additional SAP Analytics Tools ... 341

9 ... Data Warehousing ... 343

9.1 ... Do You Need Additional Data Warehouses? ... 344

9.2 ... Data Management for SAP S/4HANA ... 347

9.3 ... SAP SQL Data Warehousing with SAP HANA 2.0 ... 364

9.4 ... Big Data Warehousing ... 367

9.5 ... Summary ... 369

10 ... Business Intelligence ... 371

10.1 ... Should You Use Additional Business Intelligence Solutions? ... 371

10.2 ... SAP Analytics Suite ... 372

10.3 ... SAP Analytics Cloud ... 381

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

11.4 ... SAP S/4HANA Embedded Machine Learning ... 400

11.5 ... Summary ... 413

... Appendices ... 415

A ... Future Outlook ... 415

B ... The Authors ... 421

... Index ... 423