Architecting data and machine learning platforms

• Verfasst von: Tranquillin, Marco [VerfasserIn]
• Verfasst von: Lakshmanan, Valliappa [VerfasserIn]
• Verfasst von: Tekiner, Firat [VerfasserIn]
• Titel: Architecting data and machine learning platforms
• Titelzusatz: enable analytics and AI-driven innovation in the cloud
• Verf.angabe: Marco Tranquillin, Valliappa Lakshmanan, Firat Tekiner
• Ausgabe: First edition.
• Verlagsort: Sebastopol, CA
• Verlag: O'Reilly Media, Inc.
• Jahr: 2023
• Umfang: 1 online resource (359 pages)
• Illustrationen: illustrations
• Fussnoten: Includes index
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Applications Web - Développement
• Sach-SW: Logiciels d'application - Développement
• Sach-SW: Infonuagique
• Sach-SW: Intelligence artificielle - Informatique
• Sach-SW: Application software - Development
• Sach-SW: Artificial intelligence - Data processing
• Sach-SW: Cloud computing
• K10plus-PPN: 1868806316
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4399851880
• Lokale URL Inst.: Zum Volltext

Abstract

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.