We have firmly entered the artificial intelligence (AI) age. 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 and designed, managed and maintained, optimized and leveraged.
This book moves in two sections from the fundamentals to practical applications. In the first part, you’ll learn about the concepts that underlie product theory, the data architecture journey, and the necessary knowledge to manage products of data. The second part teaches you to put everything into practice, paying particular attention to the designing of solutions to ongoing maintenance and optimization. By the end of the book, you will have tools to begin transforming your organization’s data strategy and approach to get—and stay—ahead of the competition.
What You Will Learn
Know the evolution of data architecture and strategies
Understand the fundamentals of data product management
Know the differences between Data Product and Data as a Product
Know what the Golden Data Platform is and how to use it
Know what Data Product Management Canvas is and how to use it
Reorient your data strategy with product management principles
Understand the concepts of products and data architecture evolution in relation to your leadership
Evaluate how to solve data architecture without bias by technology
Design and implement Data as a Product during a project and ongoing
Who This Is Book Is For
Data leaders or managers who design and implement data products; product managers interested in working with data; analytics engineers, data engineers, data scientists and/or machine learning engineers implementing data solutions; data-related professionals and developers aspiring to data leadership and product management
Part I: Fundamentals for Data Product Management.- Chapter 1: Data Product Management Introduction.- Chapter 2: Data Analytical Architecture - Traditional Architecture.- Chapter 3 : Data Analytical Architecture - Big Data Architecture.- Chapter 4: Consolidating the Analytics Journey Knowledge.- Part II: Data Product Management in Practice.- Chapter 5: Golden Data Platform to Manage Data as a Product.- Chapter 6: Data Product Management.- Chapter 7: Designing the Product of Data - Understanding Phase.- Chapter 8: Designing the Product of Data - Exploring Phase.- Chapter 9: Designing the Data Product - Materializing Phase.- Chapter 10, Ownership process - Recurrent Cycle - Ongoing.
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