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Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope. This book enables organizations to truly embrace the benefits of digital transformation by anchoring data and AI products at the core of their business. It provides executives with the essential tools and concepts to establish a data and AI portfolio strategy as well as the organizational setup and agile processes that are required to deliver machine learning products at scale. Key consideration is given to advancing the data architecture and governance, balancing stakeholder needs and breaking organizational silos through new ways of working. Each chapter includes templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, manufacturing and automotive. Covering a holistic perspective on strategy, technology, product and company culture, Driving Digital Transformation through Data and AI guides the organizational transformation required to get ahead in the age of AI.
How well does your organization manage the risks associated with
information quality? Managing information risk is becoming a top
priority on the organizational agenda. The increasing
sophistication of IT capabilities along with the constantly
changing dynamics of global competition are forcing businesses to
make use of their information more effectively. Information is
becoming a core resource and asset for all organizations; however,
it also brings many potential risks to an organization, from
strategic, operational, financial, compliance, and environmental to
societal. If you continue to struggle to understand and measure how
information and its quality affects your business, this book is for
you. This reference is in direct response to the new challenges
that all managers have to face. Our process helps your organization
to understand the "pain points" regarding poor data and information
quality so you can concentrate on problems that have a high impact
on core business objectives. This book provides you with all the
fundamental concepts, guidelines and tools to ensure core business
information is identified, protected and used effectively, and
written in a language that is clear and easy to understand for
non-technical managers.
Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope. This book enables organizations to truly embrace the benefits of digital transformation by anchoring data and AI products at the core of their business. It provides executives with the essential tools and concepts to establish a data and AI portfolio strategy as well as the organizational setup and agile processes that are required to deliver machine learning products at scale. Key consideration is given to advancing the data architecture and governance, balancing stakeholder needs and breaking organizational silos through new ways of working. Each chapter includes templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, manufacturing and automotive. Covering a holistic perspective on strategy, technology, product and company culture, Driving Digital Transformation through Data and AI guides the organizational transformation required to get ahead in the age of AI.
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