SAP PRESS / Making the Case for SAP HANA
Learn about the practical applications of SAP HANA. See how SAP HANA can make a difference in a variety of business scenarios. Build a business case and get it off the ground
(Sprache: Englisch)
Everybody knows that SAP HANA makes things go faster-but if you want to implement it for your company, you need to promise more than just speed. How will it improve business processes? How will it save money? How will it save time? In this book, find out...
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Klappentext zu „SAP PRESS / Making the Case for SAP HANA “
Everybody knows that SAP HANA makes things go faster-but if you want to implement it for your company, you need to promise more than just speed. How will it improve business processes? How will it save money? How will it save time? In this book, find out what SAP HANA can really do. With case studies and high-level implementation plans from a multitude of industries, you'll learn how to build a convincing business case for any scenario. Go ahead, make your case.Highlights:
BRequirements of modern enterprise
applications
Scenarios for big data and SAP HANA
Flexible planning models
Travel cost reduction
Customer behavior analysis
Flexible and consistent data models
Service-level management automation
Sensor data evaluation
Fraud management
Health services
Galileo Press heißt jetzt Rheinwerk Verlag.
Inhaltsverzeichnis zu „SAP PRESS / Making the Case for SAP HANA “
Introduction 151 Big Data: More than Just Performance 23
1.1 What Does Big Data Mean? 25
1.2 How Do Benefits from Big Data Come About? 41
1.3 Where Are Benefits from Big Data to Be Found? 48
1.4 How Benefits Turn Into Shareholder Value 58
1.5 Evaluating Business Cases 74
2 SAP HANA: Capabilities and Limitations 87
2.1 Big Data and SAP HANA 90
2.2 Implementation Scenarios for SAP HANA 143
2.3 Trends and Future Developments 164
3 SAP HANA in Specific Industries and Business Processes 173
3.1 Creating Shareholder Value with SAP HANA 178
3.2 SAP HANA in Different Industries 181
3.3 SAP HANA in (SAP's) Business Processes 196
3.4 The Case Studies in this Book 200
4 Flexible Planning 203
4.1 What Does "Planning" Mean? 205
4.2 Scenario: Sales and Results Planning with a Multinational Tire Manufacturer 208
4.3 Planning Errors: Costs, Risks, and Opportunities 217
4.4 Solution: Monitoring Forecasts and Models in Real Time 229
4.5 Implementation Scenario and Architecture with SAP HANA 255
5 Reducing Travel Costs and Travel Times 279
5.1 Time is Money 281
5.2 Scenario: Travel Costs with an International Consulting Firm 288
5.3 One-Dimensional Optimization: Costs, Risks, and Opportunities 292
5.4 Solution: Induction Instead of Deduction 296
5.5 Implementation Scenario and Architecture with SAP HANA 307
6 Decision-Oriented Data Models 323
6.1 Data Governance: Rhetoric and Reality 325
6.2 Scenario: Determining Trade Margins in Retail 333
6.3 Inconsistent Data Models: Costs, Risks, and Opportunities 334
6.4 Solution: Generating Layers and Domains Automatically 343
6.5 Implementation Scenario and Framework Architecture with SAP HANA 372
7 Managing Customer Behavior 387
7.1 Understand, Predict, and Manage Customer Behavior 389
7.2 Scenario:
... mehr
Setting Prices in Gas Station Kiosks 393
7.3 Static Customer Segmentation: Costs, Risks, and Opportunities 394
7.4 Solution: Dynamic-Empirical Algorithms 398
7.5 Implementation Scenario and Architecture with SAP HANA 410
8 Analyzing Sensor Data Automatically and Generating Metadata 425
8.1 Handling Sensor Data 430
8.2 Scenario: Cooperation among Car Manufacturer, Telephone Company, and Insurance Firm 440
8.3 Exchanging Data: Costs, Risks, and Opportunities 441
8.4 Solution: Extracting and Managing Sensor-Specific Metadata in a Big Data Environment 447
8.5 Implementation Scenario and Framework Architecture with SAP HANA 469
9 Health Management as a Service 487
9.1 Medical Sensor Data 489
9.2 Scenario: Premium Services for the Elderly 494
9.3 Monitoring Health: Costs, Risks, and Opportunities 495
9.4 Solution: Big Data-Based Early Warning Systems 500
9.5 Implementation Scenario and Framework Architecture with SAP HANA 508
10 Detecting Fraud Automatically 515
10.1 What Does Fraud Management Mean? 518
10.2 Scenario: Theft in a Surface-Mining Operation 522
10.3 Traditional Investigation Methods: Costs, Risks, and Opportunities 522
10.4 Solution: Flexible Fraud Management Using a High-Performance Appliance 526
10.5 Implementation Scenario and Data Architecture with SAP HANA 538
11 Automating Service-Level Management 557
11.1 IT-Related Services as a Commodity 560
11.2 Scenario: Sizing an IT System 564
11.3 Sizing: Costs, Risks, and Opportunities 566
11.4 Solution: Data Linearization before Analysis 572
11.5 Implementation Scenario and Architecture with SAP HANA 580
11.6 Conclusion 586
12 Discovering Potentials, Designing Data Architectures 587
12.1 Speed Is Nothing but a Means to an End 588
12.2 SAP HANA Implementation and Data Architectures 590
12.3 Outlook: Fantasy, Creativity, Mindfulness, and Control over Data 600
The Authors 603
Index 605
7.3 Static Customer Segmentation: Costs, Risks, and Opportunities 394
7.4 Solution: Dynamic-Empirical Algorithms 398
7.5 Implementation Scenario and Architecture with SAP HANA 410
8 Analyzing Sensor Data Automatically and Generating Metadata 425
8.1 Handling Sensor Data 430
8.2 Scenario: Cooperation among Car Manufacturer, Telephone Company, and Insurance Firm 440
8.3 Exchanging Data: Costs, Risks, and Opportunities 441
8.4 Solution: Extracting and Managing Sensor-Specific Metadata in a Big Data Environment 447
8.5 Implementation Scenario and Framework Architecture with SAP HANA 469
9 Health Management as a Service 487
9.1 Medical Sensor Data 489
9.2 Scenario: Premium Services for the Elderly 494
9.3 Monitoring Health: Costs, Risks, and Opportunities 495
9.4 Solution: Big Data-Based Early Warning Systems 500
9.5 Implementation Scenario and Framework Architecture with SAP HANA 508
10 Detecting Fraud Automatically 515
10.1 What Does Fraud Management Mean? 518
10.2 Scenario: Theft in a Surface-Mining Operation 522
10.3 Traditional Investigation Methods: Costs, Risks, and Opportunities 522
10.4 Solution: Flexible Fraud Management Using a High-Performance Appliance 526
10.5 Implementation Scenario and Data Architecture with SAP HANA 538
11 Automating Service-Level Management 557
11.1 IT-Related Services as a Commodity 560
11.2 Scenario: Sizing an IT System 564
11.3 Sizing: Costs, Risks, and Opportunities 566
11.4 Solution: Data Linearization before Analysis 572
11.5 Implementation Scenario and Architecture with SAP HANA 580
11.6 Conclusion 586
12 Discovering Potentials, Designing Data Architectures 587
12.1 Speed Is Nothing but a Means to an End 588
12.2 SAP HANA Implementation and Data Architectures 590
12.3 Outlook: Fantasy, Creativity, Mindfulness, and Control over Data 600
The Authors 603
Index 605
... weniger
Bibliographische Angaben
- Autoren: Michael Mattern , Ray Croft
- 2015, 616 Seiten, mit zahlreichen Abbildungen, Maße: 18,7 x 23,7 cm, Gebunden, Englisch
- Verlag: Rheinwerk Verlag
- ISBN-10: 149321036X
- ISBN-13: 9781493210367
- Erscheinungsdatum: 16.01.2015
Sprache:
Englisch
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