Data Product Management in the AI Age
Design and Manage Your Data Strategy to Get Ahead
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We have firmly entered the age of artificial intelligence (AI). Data, the backbone of this technology, is more crucial than ever. If the algorithm is the brain, data is the content that feeds it. This book argues that to succeed in this era, organizations should adopt a holistic approach to data one that uses product management principles to inform how data is sourced, designed, managed, maintained, optimized, and leveraged.This book is divided into two sections, moving from fundamentals to practical applications. In the first part, you ll learn about the concepts that underlie product theory,...
We have firmly entered the age of artificial intelligence (AI). Data, the backbone of this technology, is more crucial than ever. If the algorithm is the brain, data is the content that feeds it. This book argues that to succeed in this era, organizations should adopt a holistic approach to data one that uses product management principles to inform how data is sourced, designed, managed, maintained, optimized, and leveraged.
This book is divided into two sections, moving from fundamentals to practical applications. In the first part, you ll learn about the concepts that underlie product theory, the data architecture journey, and the essential knowledge needed to manage data products. The second part focuses on putting everything into practice, with particular attention to designing solutions, ongoing maintenance, and optimization.
Additionally, the book introduces the Golden Data Platform and the Data Product Management Canvas, important tools and frameworks coined by author Jessika Milhomem. These resources will help you begin transforming your organization s data strategy, empowering you to stay ahead of the competition and thrive in the AI age.
What You Will Learn
Explore the evolution of data architecture and strategies
Understand the fundamentals of data product management
Differentiate between Data Product and Data as a Product
Know what the Golden Data Platform is and how to use it
Utilize the Data Product Management Canvas effectively
Reorient your data strategy with product management principles
Examine the concepts of products and data architecture evolution in relation to leadership
Evaluate how to solve data architecture without bias by technology
Design and implement Data as a Product and Data Products through a project
Maintain and enhance Data Products once launched
Who This Book is for
Undergraduates in the early semesters of their data science degrees (as it assumes no industry or programming experience); professionals (the practitioner interviews will be helpful); business leaders who want to understand what data science can do for them and the data science work being done by their teams; and career changers who want to get a good foundational understanding of the field before committing to other lea
This book is divided into two sections, moving from fundamentals to practical applications. In the first part, you ll learn about the concepts that underlie product theory, the data architecture journey, and the essential knowledge needed to manage data products. The second part focuses on putting everything into practice, with particular attention to designing solutions, ongoing maintenance, and optimization.
Additionally, the book introduces the Golden Data Platform and the Data Product Management Canvas, important tools and frameworks coined by author Jessika Milhomem. These resources will help you begin transforming your organization s data strategy, empowering you to stay ahead of the competition and thrive in the AI age.
What You Will Learn
Explore the evolution of data architecture and strategies
Understand the fundamentals of data product management
Differentiate between Data Product and Data as a Product
Know what the Golden Data Platform is and how to use it
Utilize the Data Product Management Canvas effectively
Reorient your data strategy with product management principles
Examine the concepts of products and data architecture evolution in relation to leadership
Evaluate how to solve data architecture without bias by technology
Design and implement Data as a Product and Data Products through a project
Maintain and enhance Data Products once launched
Who This Book is for
Undergraduates in the early semesters of their data science degrees (as it assumes no industry or programming experience); professionals (the practitioner interviews will be helpful); business leaders who want to understand what data science can do for them and the data science work being done by their teams; and career changers who want to get a good foundational understanding of the field before committing to other lea
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