Pipeline Pro: Building Production ETL, Batch, and Streaming Data Pipelines with Python and Airflow

Name: Pipeline Pro: Building Production ETL, Batch, and Streaming Data Pipelines with Python and Airflow
Brand: Independently Published
SKU: 9798258834829
Price: 2694.0 INR
Availability: OutOfStock

by Miguel Farmer

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ISBN13: 9798258834829
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: May 3, 2026
Pages: 430
Original Price: USD 24.99
Language: English
Edition: N/A
Item Weight: 572 grams
BISAC Subject(s): Distributed Systems / Cloud Computing

About The Book

Design, orchestrate, and scale reliable data pipelines for real world systems

Data is only valuable when it flows.

From ingestion to transformation and delivery, modern systems depend on pipelines that move data efficiently, reliably, and at scale.

"Pipeline Pro" is a practical, engineering focused guide to building production ready data pipelines using Python and orchestration tools like Apache Airflow.

This book teaches you how to design pipelines that are robust, observable, and built for real workloads.

Why production data pipelines matter

Without well designed pipelines, systems suffer from:

broken data flows
unreliable processing
lack of visibility into failures
poor scalability
inconsistent data quality

This book shows you how to build pipelines that solve these challenges.

What you will learn

fundamentals of ETL and ELT pipelines
batch vs streaming architectures
designing data workflows with Airflow
building and scheduling DAGs
data ingestion and transformation strategies
handling failures and retries
monitoring, logging, and observability
scaling pipelines for large datasets
data validation and quality checks
integrating pipelines with data warehouses and APIs

From raw data to reliable systems

Throughout the book, you will learn how to:

design end to end data pipelines
orchestrate complex workflows
process data in batch and real time
build fault tolerant systems
monitor and debug pipelines
optimize performance and cost

Each chapter focuses on practical implementation.

Practical applications

analytics data pipelines
real time data streaming systems
ETL pipelines for business intelligence
data integration platforms
machine learning data pipelines

These examples reflect real production scenarios.

Who this book is for

data engineers
backend developers
machine learning engineers
DevOps engineers working with data
professionals building data systems

If you want to build data pipelines that are reliable, scalable, and production ready, this book provides the roadmap.

Design clean flows.
Orchestrate with confidence.
Deliver data that works.

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