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portada SQL for Data Engineering. ETL, Warehousing, Cloud Platforms & AI Workflows
Type
Physical Book
Year
2026
Language
English
Pages
376
Format
Paperback
Dimensions
22.9x15.2x1.9 cm
ISBN13
9798197243744

SQL for Data Engineering. ETL, Warehousing, Cloud Platforms & AI Workflows

Masud Mondal (Author) · Independently published · Paperback

SQL for Data Engineering. ETL, Warehousing, Cloud Platforms & AI Workflows - Masud Mondal

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Synopsis "SQL for Data Engineering. ETL, Warehousing, Cloud Platforms & AI Workflows"

SQL for Data Engineering - ETL, Warehousing, Cloud Platforms & AI Workflows

Most SQL books teach you to write queries. This one teaches you to build systems.

If you know basic SQL but struggle to apply it in production environments, or you are preparing for data engineering interviews and want experience beyond simple SELECT statements, this book was written for you.

SQL for Data Engineering bridges the gap between tutorial SQL and the skills that data engineering roles actually demand - ETL pipelines, warehouse design, query optimization, and the architectural thinking that separates engineers who build reliable data systems from those who only query them.

What you will learn:

Advanced querying - joins, CTEs, subqueries, window functions, and analytical SQL patternsData transformation - cleaning, standardisation, safe casting, and deduplication techniquesETL architecture - incremental loading, staging patterns, Slowly Changing Dimensions, and idempotent pipeline designWarehouse design - star schemas, dimensional modelling, partitioning, indexing, and materialised viewsPerformance optimisation - EXPLAIN ANALYZE, execution plans, query tuning, and production-grade optimisationSemi-structured data - JSON and JSONB processing, schema drift handling, and event pipeline patternsCloud platforms - Snowflake, BigQuery, Redshift, and Databricks with practical SQL for eachAI workflows - prompt engineering for SQL tasks, AI-assisted debugging, and the risks of generated code

Four industry projects you will build:

E-Commerce Analytics WarehouseSaaS Subscription Metrics PlatformBanking Transaction Fraud Monitoring SystemFood Delivery ETL and Operations Pipeline

Each project covers a realistic business problem, complete ETL pipeline, warehouse schema, KPI queries, and interview preparation - designed to go directly into your portfolio.

You also get:

Integrated interview Q&A in every chapter drawn from real hiring panelsResume bullet points after every chapter and projectA complete career roadmap for aspiring data engineersAppendices covering SQL functions, data types, troubleshooting, glossary, and a tool landscape guide

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