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Mastering SQL for Data Engineering: A Practical Guide to SQL, Database Design, ETL Pipelines, Query Optimization, Data Warehousing, Cloud Analytics, and Real-World Projects - Brossura
Sinossi
Mastering SQL for Data Engineering is a comprehensive, hands-on guide that takes you from SQL fundamentals to advanced data engineering concepts used by leading technology companies. Whether you're a beginner or an experienced IT professional, this book provides practical explanations, real-world examples, and industry best practices to help you build scalable and efficient data solutions.
Inside this book, you'll learn how to:
- Build and manage relational databases
- Write efficient SQL queries
- Master joins, subqueries, and window functions
- Optimize SQL performance using indexes and execution plans
- Develop ETL and ELT data pipelines
- Design modern data warehouses
- Work with BigQuery, Snowflake, Redshift, Spark SQL, Hive, and Databricks
- Build real-world data engineering projects
- Prepare for SQL and Data Engineering interviews
With practical examples, mini projects, and a capstone project, this book is an ideal resource for students, software engineers, database administrators, data analysts, and aspiring data engineers looking to succeed in today's cloud-driven data ecosystem.
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Mastering SQL for Data Engineering: A Practical Guide to SQL, Database Design, ETL Pipelines, Query Optimization, Data Warehousing, Cloud Analytics, and Real-World Projects
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Mastering SQL for Data Engineering (Paperback)
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Paperback. Condizione: new. Paperback. Mastering SQL for Data Engineering is a comprehensive, hands-on guide that takes you from SQL fundamentals to advanced data engineering concepts used by leading technology companies. Whether you're a beginner or an experienced IT professional, this book provides practical explanations, real-world examples, and industry best practices to help you build scalable and efficient data solutions.Inside this book, you'll learn how to: Build and manage relational databasesWrite efficient SQL queriesMaster joins, subqueries, and window functionsOptimize SQL performance using indexes and execution plansDevelop ETL and ELT data pipelinesDesign modern data warehousesWork with BigQuery, Snowflake, Redshift, Spark SQL, Hive, and DatabricksBuild real-world data engineering projectsPrepare for SQL and Data Engineering interviewsWith practical examples, mini projects, and a capstone project, this book is an ideal resource for students, software engineers, database administrators, data analysts, and aspiring data engineers looking to succeed in today's cloud-driven data ecosystem. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798191879666
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Mastering SQL for Data Engineering : A Practical Guide to SQL, Database Design, ETL Pipelines, Query Optimization, Data Warehousing, Cloud Analytics, and Real-World Projects
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Neuware - Mastering SQL for Data Engineering is a comprehensive, hands-on guide that takes you from SQL fundamentals to advanced data engineering concepts used by leading technology companies. Whether you're a beginner or an experienced IT professional, this book provides practical explanations, real-world examples, and industry best practices to help you build scalable and efficient data solutions.Inside this book, you'll learn how to: - Build and manage relational databases- Write efficient SQL queries- Master joins, subqueries, and window functions- Optimize SQL performance using indexes and execution plans- Develop ETL and ELT data pipelines- Design modern data warehouses- Work with BigQuery, Snowflake, Redshift, Spark SQL, Hive, and Databricks- Build real-world data engineering projects- Prepare for SQL and Data Engineering interviewsWith practical examples, mini projects, and a capstone project, this book is an ideal resource for students, software engineers, database administrators, data analysts, and aspiring data engineers looking to succeed in today's cloud-driven data ecosystem. Codice articolo 9798191879666
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