Architecting Data and Machine Learning Platforms: Enable Analytics and Ai-driven Innovation in the Cloud
Author: Marco Tranquillin (Author), Valliappa Lakshmanan (Author), Firat Tekiner (Author)
Publisher finelybook 出版社: Oreilly & Associates Inc
Edition 版本: 1st
Publication Date 出版日期: 2024-01-30
Language 语言: English
Print Length 页数: 300 pages
ISBN-10: 1098151615
ISBN-13: 9781098151614
Book Description
All cloud architects need to know how to build data platforms—the key to enabling businesses with data and delivering enterprise-wide intelligence in a fast and efficient way. This handbook is ideal for learning how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, google Cloud, or multicloud tools like Fivetran, dbt, Snowflake, and Databricks.
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
About the Author
Lak works with management and data teams across a range of industries to help them employ data and AI-driven innovation to grow their businesses and increase value. Prior to this, Lak was the Director for Data Analytics and AI Solutions on google Cloud and a Research Scientist at NOAA. He is a co-author of Data Science on the google Cloud Platform, BigQuery: The Definitive Guide, and Machine Learning Design Patterns, all published by O’Reilly.
Firat is an adjunct professor at the University of Manchester and a Senior Product Manager in google Cloud. Firat has over 20 years of experience in designing and delivering bespoke information systems for some of the world’s largest research, education, telecommunications, finance and retail organizations. Following roles within National Supercomputing Services and National Centre for Text Mining, he has over 30 publications in the areas of Parallel Computing, Big Data, Artificial Intelligence and Computer Communications.