Implementing Machine Learning with SAP S/4HANA – Raghu Banda, Siar Sarferaz | buch7 – Der soziale Buchhandel
Bitte warten ...
icon suche icon merkliste icon warenkorb
Blick ins Buch
Autor/innen: Raghu Banda, Siar Sarferaz
Autor/innen: Raghu Banda, Siar Sarferaz

Implementing Machine Learning with SAP S/4HANA

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

Gebunden 11/2020
kostenloser Standardversand in DE 4 Stück auf Lager
Lieferung bis Di, 30.Nov. (ca. ¾), oder Mi , 01.Dez. (ca. ¼): bestellen Sie in den nächsten 23 Stunden, 43 Minuten mit Paketversand.

Die angegebenen Lieferzeiten beziehen sich auf den Paketversand und sofortige Zahlung (z.B. Zahlung per Lastschrift, PayPal oder Sofortüberweisung).
Der kostenlose Standardversand (2-5 Werktage) benötigt in der Regel länger als der kostenpflichtige Paketversand (1-2 Werktage). Sonderfälle, die zu längeren Lieferzeiten führen können (Bsp: Bemerkung für Kundenservice, Zahlung per Vorkasse oder Sendung ins Ausland) haben wir hier für Sie detailliert beschrieben.

Spenden icon Dank Ihres Kaufes spendet buch7 ca. 3,15 € bis 5,85 €.

Die hier angegebene Schätzung beruht auf dem durchschnittlichen Fördervolumen der letzten Monate und Jahre. Über die Vergabe und den Umfang der finanziellen Unterstützung entscheidet das Gremium von buch7.de.

Die genaue Höhe hängt von der aktuellen Geschäftsentwicklung ab. Natürlich wollen wir so viele Projekte wie möglich unterstützen.

Den tatsächlichen Umfang der Förderungen sowie die Empfänger sehen Sie auf unserer Startseite rechts oben, mehr Details finden Sie hier.

Weitere Informationen zu unserer Kostenstruktur finden Sie hier.

Benachrichtigung

Autoreninformationen

Dr. Siar Sarferaz is a chief software architect at SAP. In this role he drives digital transformation by focusing on artificial intelligence and predictive analytics. He began his career as a method researcher at Siemens AG, before moving to SAP, where he has now worked for more than 20 years, holding various positions. He is the lead architect for machine learning implementation in SAP S/4HANA and is in charge of all concepts for infusing intelligence into business processes. He studied computer science and philosophy and holds a Ph.D. in computer science.

Inhaltsverzeichnis

... Preface ... 13

... 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

Produktdetails

EAN / 13-stellige ISBN 978-1493220113
10-stellige ISBN 149322011X
Verlag Rheinwerk Verlag GmbH
Sprache Englisch
Editionsform Hardcover / Softcover / Karten
Einbandart Gebunden
Erscheinungsdatum 24. November 2020
Seitenzahl 408
Format (L×B×H) 26,0cm × 18,4cm × 2,9cm
Gewicht 1004g
Warengruppe des Lieferanten Naturwissenschaften - Informatik, EDV
Mehrwertsteuer 7% (im angegebenen Preis enthalten)
Bestseller aus dieser Kategorie

Naturwissenschaften - Informatik, EDV

Noch nicht das passende gefunden?
Verschenken Sie einfach einen Gutschein.

Auch hier werden natürlich 75% des Gewinns gespendet.

Gutschein kaufen

Was unsere Kund/innen sagen:

Impressum Datenschutz Hilfe / FAQ