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Avoid being left behind and make data science and artificial intelligence a profitable part of your business with this practical guide to product delivery.
List of contents
Chapter - 01: Introduction to delivering data and AI products; Chapter - 02: Developing the data and AI product strategy and goals; Chapter - 03: Setting up the data and AI product delivery organization; Chapter - 04: Identifying and defining data and AI products; Chapter - 05: Delivering high quality data and AI products; Chapter - 06: Designing the data and AI platform and architecture; Chapter - 07: Driving transformative change with data and AI products; Chapter - 08: The future of data and AI products in your organization
About the author
Dr Alexander Borek is an independent advisor for data, analytics and machine learning strategy. He was previously the Global Head of Data, Analytics & AI at Volkswagen Financial Services, scaling data products across international markets. In his previous roles, he led the data transformation at Volkswagen Group and worked as management consultant at Gartner and IBM.
Dr Nadine Prill is Head of Product at Taktile, a Berlin based tech company that provides a platform for machine learning model deployment, governance and explainability. Previously, she worked as product manager at PricewaterhouseCoopers (PwC). She holds a PhD from the University of Oxford.
Summary
Leading digital businesses such as Netflix, Amazon and Uber use data science and machine learning at scale in all of their core business processes, but many organizations struggle to expand their projects beyond a small pilot scope. This book enables all organizations to realize the promised value of these projects.
This book explains the step-by-step processes around creating an effective data and AI product portfolio strategy, establishing delivery processes, and maturing the digital architecture and platform in a hybrid cloud environment. Key consideration is given to the challenges of obtaining buy-in from senior stakeholders, breaking organizational silos through knowledge sharing and using data and AI education as a powerful method for driving change.
Each chapter includes tools and templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, technology and automotive. With coverage of security, data protection and compliance, Driving Digital Transformation through Data and AI enables the organizational transformation required to get ahead in the age of artificial intelligence and digital disruption.
Foreword
Provides key principles for sharing knowledge, educating staff on data and AI, and effectively engaging top executives
