Overview

Unlock the Full Power of ETL in the Cloud Era-Build Scalable, Efficient Data Pipelines That Drive Real Results In today's data-driven world, messy and fragmented data is a bottleneck to growth. ETL Data Pipelines Demystified 2026 is your complete roadmap to mastering Extract, Transform, Load (ETL) systems-from legacy infrastructure to modern, cloud-native architectures. Whether you're a beginner, an experienced data engineer, or transitioning into analytics from another field, this book is your guide to designing pipelines that are clean, efficient, and built for real-world use. If you've struggled to choose between ETL and ELT, felt overwhelmed by tools like Airflow, dbt, or Spark, or you want to future-proof your career with hands-on skills and project-ready knowledge, this book will transform your understanding. Inside this actionable guide, you'll learn how to: Understand the building blocks of ETL-extraction, transformation, and loading-in both batch and real-time environments Navigate structured, semi-structured, and unstructured data from sources like APIs, files, and databases Choose the right tools: Spark, Apache Airflow, dbt, Nifi, Fivetran, and more Implement best practices for data cleaning, modeling, lineage tracking, and schema evolution Load data into modern destinations like Snowflake, BigQuery, Redshift, and Delta Lake Master workflow orchestration, monitoring, logging, and fault recovery Integrate ETL with machine learning pipelines, reverse ETL flows, and data governance frameworks Build a resume-ready portfolio and gain clarity on certifications and hands-on labs that boost your value What sets this book apart? Written for 2026 and beyond-aligned with the latest trends in modern data stacks Covers serverless and hybrid ETL, including AWS Glue, Azure Data Factory, and CI/CD with GitOps Includes a capstone project: design and deploy a production-grade, cloud-based ETL pipeline with orchestration and monitoring Perfect for: Data engineers, analytics engineers, software developers, cloud architects, business intelligence professionals, and career-changers ready to break into the data field.

Full Product Details

9798253051856

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available