Architecting Data and Machine Learning Platforms: Enable Analytics and Ai-Driven Innovation in the Cloud (Paperback)

Tranquillin, Marco, Lakshmanan, Valliappa, Tekiner, Firat

  • 出版商: O'Reilly
  • 出版日期: 2023-11-21
  • 定價: $2,290
  • 售價: 9.5$2,176
  • 貴賓價: 9.0$2,061
  • 語言: 英文
  • 頁數: 359
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1098151615
  • ISBN-13: 9781098151614
  • 相關分類: Machine Learning
  • 立即出貨 (庫存 < 4)



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


所有雲架構師都需要知道如何建立數據平台,這是實現企業數據能力和提供企業級智能的關鍵,並以快速高效的方式交付。本手冊非常適合學習如何使用AWS、Azure、Google Cloud或多雲工具(如Fivetran、dbt、Snowflake和Databricks)設計、構建和現代化雲原生數據和機器學習平台。

作者Marco Tranquillin、Valliappa Lakshmanan和Firat Tekiner在雲環境中涵蓋了整個數據生命周期,從數據輸入到激活,並使用真實的企業架構。您將學習如何轉換和現代化熟悉的解決方案,如數據倉庫和數據湖,並能夠利用最新的AI/ML模式獲得準確且更快的洞察力,以獲得競爭優勢。

- 設計現代化的雲原生或混合數據分析和機器學習平台
- 通過在數據平台中整合企業數據來加速以數據為導向的創新
- 民主化企業數據的訪問權限,使業務團隊能夠提取洞察力並構建AI/ML能力
- 使用流水線實現實時決策能力,從描述性分析方法轉向更具預測性和指導性的方法,構建MLOps平台
- 使您的組織在雲環境中更有效地使用數據分析和機器學習技術