
Sách Architecting Data and Machine Learning Platforms Enable Analytics and AI-Driven Innovation in the Cloud (sách keo gáy, bìa mềm)
All cloud architects need to know how to build data
platforms that enable businesses to make data-driven decisions and
deliver enterprise-wide intelligence in a fast and efficient way. This
handbook shows you how to design, build, and modernize cloud native data
and machine learning platforms using AWS, Azure, Google Cloud, and
multicloud tools like Snowflake and Databricks.
Authors Marco
Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire
data lifecycle from ingestion to activation in a cloud environment using
real-world enterprise architectures. You’ll learn how to transform,
secure, 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.
You’ll learn how to:
• Design a modern and secure cloud native or hybrid data analytics and machine learning platform
• Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform
• Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities
• Enable your business to make decisions in real time using streaming pipelines
• Build an MLOps platform to move to a predictive and prescriptive analytics approach
Categories:Computers - Artificial Intelligence (AI)
Year:2023
Edition:1
Language:english
Pages:362