
Implementing Machine Learning with SAP S/4HANA
Description
Put machine learning to work in SAP S/4HANA! Get started by reviewing your available tools and implementation options. Then, learn how to set up services, train models, and manage applications. Discover how machine learning is implemented in key lines of business, from finance to sales. With details on extensibility and related SAP Cloud Platform services, you'll find everything you need to make the most of machine learning!
In this book, you'll learn about:
a. Tools and Technologies
Get to know the machine learning toolkit you can use to consume models: SAP HANA, SAP Cloud Platform, SAP Analytics Cloud, SAP Intelligent Robotic Process Automation, and more.
b. Technical Implementation
Perform the technical setup in SAP S/4HANA. Learn how to implement key services, train machine learning models, and manage applications, from data integration to user interface design.
c. Business Implementation
See how machine learning improves your lines of business. Explore machine learning in SAP S/4HANA business processes for finance, procurement, sales, inventory, and more.
Highlights Include:
1) Predictive analytics
2) Predictive intelligence
3) Tools and technologies
4) Architecture
5) Embedded services
6) Technical implementation
7) Business implementation
8) Extensibility
9) SAP HANA
10) SAP Cloud Platform
11) SAP Analytics Cloud
More details
Persons
Content
... What Is the Impact of Machine Learning? ... 13
... What Ethical Aspects Will Be Considered? ... 14
... What Is the Objective of This Book? ... 16
... What Is the Target Audience for This book? ... 18
1 ... Introduction to Predictive Intelligence ... 19
1.1 ... The Intelligent Enterprise ... 19
1.2 ... How Predictive Intelligence Is Evolving at SAP ... 22
1.3 ... Connected End-to-End Scenarios ... 24
1.4 ... Analytics of the Future ... 32
1.5 ... Summary ... 37
2 ... The Evolution of Predictive Analytics and Machine Learning at SAP ... 39
2.1 ... Predictive Analytics and Machine Learning before SAP S/4HANA ... 39
2.2 ... Technologies and Methodologies ... 40
2.3 ... Best Practices ... 45
2.4 ... Summary ... 48
3 ... Tools, Technologies, and Services ... 49
3.1 ... Machine Learning and Predictive Analytics Approaches ... 49
3.2 ... Embedded Machine Learning and Predictive Analytics ... 51
3.3 ... SAP Cloud Platform ... 57
3.4 ... SAP Analytics Cloud ... 63
3.5 ... SAP Intelligent Robotic Process Automation ... 70
3.6 ... SAP Internet of Things ... 76
3.7 ... Summary ... 80
4 ... Architecture ... 83
4.1 ... Introduction ... 83
4.2 ... Architecture Overview ... 90
4.3 ... Embedded Machine Learning ... 97
4.4 ... Side-by-Side Machine Learning ... 102
4.5 ... Side-by-Side Predictive Analytics ... 114
4.6 ... Summary ... 118
5 ... Technical Implementation ... 119
5.1 ... Approach Comparison ... 119
5.2 ... Implementing Embedded Machine Learning Applications ... 122
5.3 ... Implementing Side-by-Side Machine Learning Applications ... 137
5.4 ... Implementing Side-by-Side Predictive Analytics Applications ... 148
5.5 ... Application Management Processes ... 155
5.6 ... Summary ... 260
6 ... Business Implementation ... 261
6.1 ... Overview of Intelligent Scenarios ... 261
6.2 ... Configuration Basics ... 266
6.3 ... Finance ... 272
6.4 ... Sourcing and Procurement ... 295
6.5 ... Inventory and Supply Chain ... 308
6.6 ... Sales ... 317
6.7 ... Research and Development/Engineering ... 323
6.8 ... Industries ... 327
6.9 ... Summary ... 374
7 ... Services on SAP Cloud Platform ... 375
7.1 ... Key Trends and Capabilities ... 375
7.2 ... SAP Data Intelligence ... 382
7.3 ... Machine Learning ... 383
7.4 ... Internet of Things ... 386
7.5 ... Blockchain ... 387
7.6 ... Summary ... 388
8 ... The Road Ahead and Further Learning ... 389
8.1 ... Upcoming Features and Functionality ... 389
8.2 ... Blogs for Continuous Information ... 392
8.3 ... Summary ... 393
... The Authors ... 395
... Index ... 397