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Cover for BigQuery Foundations and Advanced Techniques: Definitive Reference for Developers and Engineers

BigQuery Foundations and Advanced Techniques: Definitive Reference for Developers and Engineers

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Inglês
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"BigQuery Foundations and Advanced Techniques"

Unlock the full potential of Google BigQuery with "BigQuery Foundations and Advanced Techniques," the definitive guide for data engineers, architects, and analytics professionals seeking to master serverless cloud data warehousing. This comprehensive volume delves deep into BigQuery’s architecture, exploring its serverless design, storage model, and tightly integrated GCP ecosystem. Readers will gain a clear understanding of data organization strategies, resource management, and robust API options, establishing a strong foundation for building scalable analytics solutions.

Building on these core concepts, the book expertly navigates through essential practices in schema design, partitioning, clustering, and data lake architecture, empowering users to manage massive datasets efficiently. Practical, hands-on chapters cover batch and streaming ingestion, sophisticated ETL/ELT workflows, and advanced query optimization techniques—including the use of BigQuery’s SQL extensions, UDFs, materialized views, and caching mechanisms. The reader will also find invaluable insights into operational excellence, encompassing monitoring, automation, spend management, and CI/CD for modern analytics pipelines.

Going beyond the fundamentals, the guide addresses advanced topics such as identity management, data protection, regulatory compliance, and fine-grained security, ensuring enterprise-grade governance. Readers will also explore the frontiers of analytics, from BigQuery ML and geospatial analysis to federated queries and hybrid cloud interoperability. Rounded out with best practices, anti-patterns, migration strategies, and a forward-looking perspective on data warehousing trends, "BigQuery Foundations and Advanced Techniques" is essential reading for professionals aiming to lead and innovate in today’s cloud analytics landscape.

© 2025 NobleTrex Press (Ebook): 6610000832057

Data de lançamento

Ebook: 5 de junho de 2025

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