Many organizations use enterprise software that incorporates rule-based processing to automate business tasks, enable compliance, and ensure data consistency.
While rule-based automation has increased efficiency for businesses, it can be limited as the software doesn’t have the ability to learn and improve as humans do. An intelligent enterprise overcomes this by automating a majority of the repetitive tasks in its day-to-day business processes. It does this by applying innovative intelligent technologies like machine learning and AI.
SAP is leveraging the rise of AI through its intelligent enterprise initiative, to help companies of all sizes and industries manage today’s digital marketplace. For example, after automating the invoice-matching process, accountants no longer need to spend their time manually assigning incoming payments to outstanding invoices. Instead, they can focus on other tasks.
Machine Learning
Machine learning is a subset of AI that uses self-learning algorithms to find patterns in both structured and unstructured data in an effort to improve enterprise software. It allows for much faster process improvements without the need for human intervention and program-explicit rules, as the algorithms are used to predict outputs. Machine learning makes sense of raw data and discovers hidden insights and relationships by continuously learning.
Companies utilizing machine learning can benefit from cost savings, improved forecasting, optimized operations, more personalized customer service, and enhanced user experience. Consider this example in reference to the manufacturing industry: failure of high-tech equipment.
This is a business-critical issue. By combining sensor data with business information in ERP systems and applying machine learning models, the health of these machines can be monitored and even predicted. Thus, maintenance scheduling and logistics planning for spare parts and repair crew management can be transformed into a proactive business process.
The Implementing Machine Learning with SAP S/4HANA Book
For those looking to improve their business processes with intelligent technologies like machine learning, we’ve published Implementing Machine Learning with SAP S/4HANA to help businesses get started.
Start off with an introduction to predictive intelligence as a component of the SAP intelligent enterprise. You’ll learn about its evolution at SAP with a focus on predictive analytics and machine learning, diving deep into how these technologies were implemented in SAP landscapes prior to SAP S/4HANA. You’ll then be prepared to explore how these technologies, methodologies, and best practices were adapted for SAP S/4HANA systems.
You’ll move on to the tools and services that can be used for machine learning in SAP S/4HANA. From there, you’ll get a brief overview of topics like intelligent robotic process automation, Internet of Things, and more. You’ll gain insight into the solution architecture of SAP S/4HANA with machine learning.
You’ll walk through technical and business implementations next. The book describes how to set up the services and training models for both embedded and side-by-side machine learning, and also explores application management. Then, you’ll discover how machine learning and predictive analytics can be applied to specific business processes and how they solve problems within various lines of business. You’ll take a tour of the SAP Cloud Platform services at a high level and become familiarized with the full scope of services related to machine learning. To wrap up, you’ll get details about how to access support resources and learn about the roadmap for machine learning in SAP S/4HANA.
Who Is This Book For?
This book is for anyone interested in applied machine learning based on SAP S/4HANA. There are various target groups who will find this title beneficial, including architects building software designs, developers looking to implement their own applications based on the SAP S/4HANA platform, consultants who want to configure the delivered SAP S/4HANA business applications for machine learning and predictive analytics, and end users who want to consume SAP S/4HANA business applications based on machine learning and predictive analytics capabilities.
About the Authors
Dr. Siar Sarferaz is a chief software architect at SAP. In this role, he drives digital transformation by focusing on AI and predictive analytics. He began his career as a method researcher at Siemens AG, before moving to SAP, where he has 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.
Raghu Banda is a senior director of AI product strategy at SAP Labs, where he is responsible for infusing AI technologies in SAP S/4HANA. He began his career as a software developer and architect in India before moving to the US in 1997. He joined with SAP in 2001 and worked in various roles such as engineering development, customer support and implementations, product marketing, and product management. He has worked with predictive analytics and machine learning since SAP entered this arena in 2012. He holds a Bachelor of Science in computer science and engineering and will soon graduate from the prestigious INSEAD business school. He is the lead product manager for leveraging machine learning into SAP S/4HANA.
How to Purchase
If you’re interested in purchasing Implementing Machine Learning with SAP S/4HANA, follow this link and choose the format that works best for you: e-book, print edition, or bundle (both e-book and print).
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