Are you ready to master the essential skills that power modern data-driven organizations? This book offers a clear, practical guide to using Python to design, build, and maintain scalable data pipelines that transform raw data into actionable insights. Whether you want to automate workflows, handle large datasets, or integrate machine learning, this book equips you with the tools and techniques required to excel in data engineering and analytics. Python for Data Engineering and Analytics covers the full lifecycle of data workflows, from ingestion and cleaning to transformation, storage, and analysis. You will learn how to work effectively with diverse data sources, connect to relational and NoSQL databases, build reliable ETL/ELT pipelines, and orchestrate workflows using tools like Apache Airflow. The book also explores big data processing with PySpark and Dask, real-time streaming architectures, cloud data platforms, and best practices in security, governance, and testing. What sets this book apart is its structured approach, blending foundational concepts with hands-on examples and real-world projects. Key chapters include: Foundations of Data Engineering and Analytics : Understand the role of Python and the landscape of data workflows. - Data Acquisition and Ingestion : Learn to handle CSV, JSON, Parquet, databases, APIs, and streaming data. - Pipeline Construction and Automation : Build, schedule, and monitor pipelines using native Python, Airflow, Prefect, and Luigi. - Big Data and Cloud Integration : Scale your pipelines with PySpark, Dask, and cloud services from AWS, Azure, and GCP. - Analytics, Visualization, and Machine Learning : Perform exploratory data analysis, create dashboards, and prepare data for ML models. - Security, Governance, and Testing : Implement robust logging, error handling, CI/CD, and compliance best practices. Packed with code examples, practical tips, and case studies, this book is designed for developers, data engineers, and analysts who want to build efficient, maintainable, and scalable data systems using Python. Take control of your data workflows and turn complexity into clarity. Whether you’re starting out or expanding your skills, this book will guide you every step of the way. Start building smarter data pipelines today—add this essential guide to your library.
