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Title details for Modern Data Architecture on Google Cloud by Gopal Sahu - Wait list

Modern Data Architecture on Google Cloud

by Gopal Sahu
ebook
Modernize on-premise systems and build data systems from scratch that support data intensive analytics on Google Cloud Platform with this guide.

Key Features
  • Learn to take advantage of GCP features to build modern data systems
  • Enhance your design decisions for modernizing on-premise systems on Google Cloud
  • Build a solid foundation of various data architectures like Data Lake, Data Mesh, Data Lakehouse and implement them using GCP
    • Book DescriptionData is a key asset for organizations in this era of digitization. Harnessing the insights from data is a key challenge as data is generated at high speed and volume. Use cases like advanced analytics, real-time analytics, and data science applications need data to be gathered and processed at scale. With the flexibility and advanced features of the public cloud, organizations are moving their existing data systems to the cloud or building future-ready data platforms. GCP is one of the leading cloud providers with a huge catalog of data services. GCP uses the same infrastructure that powers Google Search, YouTube, Gmail, etc. This book is a field guide that helps you build modern platforms on GCP. The book starts by going deep into the fundamentals of data architectures, then takes a hands-on approach to create a unified design for future-ready data platforms, and concludes with best practices for scalability and cost. This book offers a balanced approach of theoretical concepts and hands-on exercises to help readers learn to make decisions for selecting cloud services and technologies for architecture design and implementation. By the end of the book you'll be able to build Data Architectures using GCP and scale them by Implementing systems for data analysis, visualisation, AI & MLWhat you will learn
  • Learn how to build Data platforms from scratch on GCP
  • Gain deeper understanding of various data architectures like Data Warehouse, Data Lake, Data Vault, Data Mesh & Data Lakehouse
  • Take decisions on choosing various services and technologies for the data platform
  • Implement enterprise level features of a data platform like data quality, data governance and compliance
  • Build complex DevOps and MLOps systems on GCP
  • Implementing data observability, logging, monitoring for the overall system
  • Learn best practices for various services and optimizing for cost on GCP
    • Who this book is for

    If you are a data architect who wants to gain expertise in building enterprise ready data architectures on GCP, this book is an excellent handbook with hands-on examples for building it from scratch as well as take decisions while modernizing an on-premise data system onto Google Cloud.

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    subjects

    Languages

    • English