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Summary
Summary
Building Intelligent Enterprises by leveraging the emerging and next-generation technologies to accelerate the adoption of digital transformation
The speed of innovation and emerging IT technologies are changing at a very fast pace and enterprises are eager to join the digital revolution so they can stand above the competition and succeed as the enterprise of tomorrow. This book is an attempt to make the enterprise intelligent by providing the path to digital transformation and the adoption of new IT methods, tools and technologies.
This book has been organized to cover the following topics: Digital Transformation, Design Thinking, Agile, DevOps, Robotic Process Automation, Internet of Things, Artificial Intelligence, Machine Learning, Blockchain, Drones, Augmented and Virtual Reality, 3D Printing, Big Data, Analytics, Cloud Computing, APIs, and SAP Leonardo. No prior knowledge of any technical coding or language is necessary to understand the content of this book.
End-to-end storyline to accelerate the enterprise's digital transformation journey How an enterprise can stay relevant, compete, and perform in the digital economy How to leverage these technologies to build intelligent enterprises Understand and apply the emerging technologies across key business processes Industry-specific Use Cases for all technologies as a reference point to build the business case for implementationThe book is very well suited towards the C-Suite executives, both IT and business leaders, directors and managers, project managers, solution architects, and all professionals who have an interest and desire to keep up-to-date with the latest technological trends, looking for a career change, want to help enterprise adapt and onboard the digital roadmap, or have an agenda to digitize key processes within the enterprise to make it intelligent.
Author Notes
ANUP MAHESHWARI is an SAP S/4HANA Finance, Business and Digital Transformation thought leader. He has over 21 years of IT and business consulting experience at firms such as IBM, Deloitte, and Accenture. He is the author of Implementing SAP S/4HANA Finance . Anup received his Masters of Science from The George Washington University and is a Stanford Certified Project Manager and a PMI Certified Project Management Professional (PMP). Anup also has an Enterprise Architect Certificate from Carnegie Mellon University. He is a Chartered Financial Analyst, an MBA, and a Certified SAP S/4HANA Consultant.
Table of Contents
Preface | p. xi |
About this Book | p. xiii |
Acknowledgments | p. xix |
Part I Introduction | p. 1 |
Chapter 1 Digital Transformation | p. 3 |
Digital Transformation | p. 3 |
Digital Transformation Impact | p. 8 |
Value Drivers | p. 9 |
Digital Implementation Methodology | p. 10 |
Emerging Technology Heatmap | p. 13 |
Emerging Digital Themes by Industry | p. 15 |
Conclusion | p. 26 |
Part II Collaborative Methods and Tools | p. 27 |
Chapter 2 Design Thinking | p. 29 |
Design Thinking Overview | p. 29 |
Design Thinking Methodology | p. 31 |
Tools and Techniques | p. 35 |
Use Cases | p. 41 |
Conclusion | p. 43 |
Chapter 3 Agile | p. 45 |
Agile Overview | p. 45 |
Agile Methodology | p. 48 |
Agile Tools | p. 49 |
Conclusion | p. 51 |
Chapter 4 DevOpS | p. 53 |
DevOps Overview | p. 53 |
DevOps Enterprise Maturity | p. 56 |
DevOps Enablers | p. 57 |
Adoption by industry | p. 59 |
Use Cases | p. 62 |
Conclusion | p. 63 |
Part III Intelligent Technologies | p. 65 |
Chapter 5 Robotic Process Automation | p. 67 |
Robotic Process Automation (RPA) Overview | p. 67 |
Automation Capabilities | p. 69 |
Enterprise RPA Architecture | p. 74 |
Enterprise RPA Model | p. 76 |
Enterprise RPA Implementation Methodology | p. 78 |
Potential Automation Opportunities | p. 81 |
RPA Opportunities by Industry | p. 82 |
RPA Opportunities by Function | p. 89 |
Use Cases | p. 96 |
Conclusion | p. 98 |
Chapter 6 Internet of Things | p. 99 |
Internet of Things Overview | p. 99 |
Understanding IoT Architecture | p. 105 |
IoT Implementation Methodology | p. 119 |
New Era with Connected Devices | p. 121 |
IoT Applications by Industry | p. 129 |
Use Cases | p. 135 |
Conclusion | p. 139 |
Chapter 7 Artificial Intelligence | p. 141 |
Artificial Intelligence (AI) Overview | p. 141 |
AI Capabilities | p. 147 |
Enterprise AI Architecture | p. 154 |
Enterprise AI Implementation Methodology | p. 157 |
Potential AI Opportunities | p. 160 |
AI Opportunities by Industry | p. 161 |
AI Opportunities by Functional Area | p. 171 |
Use Cases | p. 175 |
Conclusion | p. 178 |
Chapter 8 Machine Learning | p. 179 |
Machine Learning Overview | p. 179 |
Machine Learning Algorithms | p. 182 |
Enterprise Machine Learning Model | p. 183 |
Machine Learning Implementation Methodology | p. 184 |
Machine Learning Solutions by Industry | p. 186 |
Use Cases | p. 187 |
Conclusion | p. 189 |
Chapter 9 Blockchain | p. 191 |
Blockchain Overview | p. 191 |
Understanding Blockchain Architecture | p. 197 |
Smart Contracts in Blockchain | p. 204 |
Blockchain Execution Roadmap | p. 205 |
Blockchain Security | p. 207 |
Challenges of Blockchain-enabled Transformation | p. 209 |
Applications of Blockchain | p. 209 |
Use Cases of Blockchain | p. 211 |
Key Players | p. 218 |
Conclusion | p. 219 |
Chapter 10 Drones | p. 221 |
Drones Overview | p. 221 |
Drones as Data Collector | p. 224 |
Risk Considerations | p. 225 |
Drone Applications | p. 226 |
Opportunities by Industry | p. 227 |
Use Cases | p. 232 |
Conclusion | p. 233 |
Chapter 11 Virtual Reality | p. 235 |
Augmented and Virtual Reality Overview | p. 235 |
AR and VR in the Current Ecosystem | p. 237 |
Understanding AR/VR Architecture | p. 237 |
Platform | p. 248 |
Security and Privacy | p. 249 |
Opportunities by Industry | p. 251 |
Use Cases | p. 257 |
Conclusion | p. 258 |
Chapter 12 3D Printing | p. 259 |
3D Printing Overview | p. 259 |
Methodology | p. 262 |
Use Cases | p. 263 |
Conclusion | p. 265 |
Chapter 13 Big Data | p. 267 |
Big Data Overview | p. 267 |
Big Data Technology | p. 273 |
Understanding Big Data Architecture | p. 278 |
Big Data Opportunities by Industry | p. 285 |
Use Cases | p. 285 |
Conclusion | p. 290 |
Chapter 14 Analytics | p. 291 |
Analytics Overview | p. 291 |
Analytics Components | p. 294 |
Analytics Methodology | p. 294 |
Analytics Techniques | p. 296 |
Use Cases | p. 301 |
Conclusion | p. 303 |
Part IV Digital Infrastructure | p. 305 |
Chapter 15 Cloud Computing | p. 307 |
Cloud Overview | p. 307 |
Enterprise Cloud Transformation Methodology | p. 319 |
Enterprise Cloud Migration Framework | p. 322 |
Enterprise Strategy and Roadmap to Cloud | p. 324 |
Enterprise Migration Path to Cloud | p. 327 |
Key Cost Drivers | p. 330 |
Enterprise Transformation to the Cloud | p. 332 |
Enterprise Cloud Management and Optimization | p. 336 |
Use Cases | p. 339 |
Conclusion | p. 342 |
Chapter 16 APIs | p. 343 |
API Overview | p. 343 |
API Architecture | p. 345 |
API Business Strategy | p. 347 |
API Life Cycle and Roadmap | p. 349 |
Conclusion | p. 352 |
Part V Product Review | p. 353 |
Chapter 17 SAP Leonardo | p. 355 |
SAP S/4HANA ERP Overview | p. 355 |
Understanding SAP Leonardo | p. 356 |
SAP Leonardo Internet of Things | p. 357 |
SAP Leonardo Machine Learning | p. 362 |
SAP Leonardo Blockchain | p. 366 |
SAP Leonardo Big Data | p. 367 |
SAP Leonardo Data Intelligence | p. 368 |
SAP Leonardo Analytics | p. 368 |
SAP Leonardo Enterprise Engagement | p. 369 |
Conclusion | p. 371 |
About the Author | p. 373 |
Index | p. 375 |