Architecting data and machine learning platforms: enable analytics and ai-driven...
Описание
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
Також купити книгу Architecting Data and Machine Learning Platforms: Enable
Analytics and AI-Driven Innovation in the Cloud, Marco Tranquillin, Valliappa
Lakshmanan, Firat Tekiner, more Ви можете по посиланню
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