E-Books →Architecting Data and Machine Learning Platforms (Third Early Release)

Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle in a cloud environment, from ingestion to activation, using real-world enterprise architectures. You'll learn how to transform and modernize familiar solutions, like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage.
This book shows you how to
Design a modern cloud native or hybrid data analytics and machine learning platform
Accelerate data-led innovation by consolidating enterprise data in a data platform
Democratize access to enterprise data and allow business teams to extract insights and build AI/ML capabilities
Enable your business to make decisions in real time using streaming pipelines
Move from a descriptive analytics approach to a more predictive and prescriptive one by building an MLOps platform
Make your organization more effective in working with data analytics and machine learning in a cloud environment