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Mastering SQL with GCP BigQuery
"Mastering SQL with GCP BigQuery" is an in-depth guide designed to help you leverage the power of Google Cloud’s BigQuery for extensive data analytics. Whether you're a novice in SQL or a seasoned data professional, this book offers a thorough exploration of how to manage, query, and analyze large datasets using BigQuery’s serverless, highly scalable architecture.
Key Topics
Getting Started with Google Cloud and
Setting up your Google Cloud account and configuring BigQuery.Navigating the BigQuery user interface and understanding its core components.Crafting Efficient SQL
Writing fundamental SQL queries to filter, sort, and aggregate data.Advanced querying techniques including subqueries, Common Table Expressions (CTEs), and recursive queries.Combining and Analyzing
Utilizing JOINs to merge datasets and perform complex analytics.Employing advanced window functions to perform cumulative and ranking calculations.Optimizing
Leveraging BigQuery’s partitioning and clustering features to enhance query performance and reduce costs.Implementing best practices for query optimization, including using materialized views and understanding query execution plans.Managing Large
Techniques for handling massive datasets efficiently.Configuring and managing data access, roles, and permissions to ensure data security.Using encryption and data governance practices to protect sensitive information.Real-Time Analytics and Predictive
Running real-time data analytics and integrating BigQuery with other Google Cloud services.Building and deploying machine learning models with BigQuery ML to make data-driven predictions.Case Studies and Practical
Real-world case studies showcasing how businesses have utilized BigQuery for various data challenges.Hands-on examples and exercises to solidify your understanding and apply concepts to practical scenarios.This comprehensive resource is ideal for data analysts, data engineers, and cloud architects looking to enhance their BigQuery skills and fully exploit its capabilities. By mastering the techniques and strategies presented in this book, you’ll be able to unlock actionable insights, optimize data processing performance, and achieve cost-effective data management.
Key Topics
Getting Started with Google Cloud and
Setting up your Google Cloud account and configuring BigQuery.Navigating the BigQuery user interface and understanding its core components.Crafting Efficient SQL
Writing fundamental SQL queries to filter, sort, and aggregate data.Advanced querying techniques including subqueries, Common Table Expressions (CTEs), and recursive queries.Combining and Analyzing
Utilizing JOINs to merge datasets and perform complex analytics.Employing advanced window functions to perform cumulative and ranking calculations.Optimizing
Leveraging BigQuery’s partitioning and clustering features to enhance query performance and reduce costs.Implementing best practices for query optimization, including using materialized views and understanding query execution plans.Managing Large
Techniques for handling massive datasets efficiently.Configuring and managing data access, roles, and permissions to ensure data security.Using encryption and data governance practices to protect sensitive information.Real-Time Analytics and Predictive
Running real-time data analytics and integrating BigQuery with other Google Cloud services.Building and deploying machine learning models with BigQuery ML to make data-driven predictions.Case Studies and Practical
Real-world case studies showcasing how businesses have utilized BigQuery for various data challenges.Hands-on examples and exercises to solidify your understanding and apply concepts to practical scenarios.This comprehensive resource is ideal for data analysts, data engineers, and cloud architects looking to enhance their BigQuery skills and fully exploit its capabilities. By mastering the techniques and strategies presented in this book, you’ll be able to unlock actionable insights, optimize data processing performance, and achieve cost-effective data management.
Kindle Edition
Published September 17, 2024
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