,Data Engineering Made Simple: Your Friendly
Guide to SQL, Python, and PySpark.
A book by - Brahma Reddy Katam
Preface
Welcome to " Data Engineering Made Simple: Your
Friendly Guide to SQL, Python, and PySpark." This
book is here to help you understand everything you
need to know about data engineering, from the basics
to advanced techniques. Whether you're just starting
,out or looking to deepen your knowledge, this book
offers practical guidance and real-world examples to
help you become a skilled data engineer.
Contents
Introduction
1. Welcome to Data Engineering
- What is Data Engineering?
- Why SQL, Python, and PySpark?
- How to Use This Book
- Setting Up Your Environment
Part 1: SQL
2. Getting Started with SQL
- What is SQL?
- Setting Up a Database
- Basic SQL Commands
3. Working with Databases
- Creating Databases and Tables
- Inserting, Updating, and Deleting Data
- Querying Data with SELECT
4. Advanced SQL Concepts
- Joins and Subqueries
- Aggregations and Group By
- Indexes and Performance Tips
5. SQL in Action
- Building a Small Database Project
- Real-World SQL Scenarios
, Part 2: Python
6. Introduction to Python
- Python Basics: Variables and Data Types
- Setting Up Python for Data Engineering
- Essential Python Libraries
7. Data Manipulation with Python
- Working with Pandas
- Reading and Writing Data
- Data Cleaning and Transformation
8. Automation with Python
- Writing Scripts for Automation
- Scheduling and Running Scripts
9. Python in Action
- Building Data Pipelines
- Real-World Python Scenarios
Part 3: PySpark
10. Introduction to PySpark
- What is PySpark?
- Setting Up PySpark
- Basics of RDDs and DataFrames
11. Data Processing with PySpark
- Loading and Transforming Data
- ETL Processes with PySpark
- Using Spark SQL
12. Advanced PySpark
- Optimization and Performance
- Integrating with Hadoop and Hive
- Streaming Data
Guide to SQL, Python, and PySpark.
A book by - Brahma Reddy Katam
Preface
Welcome to " Data Engineering Made Simple: Your
Friendly Guide to SQL, Python, and PySpark." This
book is here to help you understand everything you
need to know about data engineering, from the basics
to advanced techniques. Whether you're just starting
,out or looking to deepen your knowledge, this book
offers practical guidance and real-world examples to
help you become a skilled data engineer.
Contents
Introduction
1. Welcome to Data Engineering
- What is Data Engineering?
- Why SQL, Python, and PySpark?
- How to Use This Book
- Setting Up Your Environment
Part 1: SQL
2. Getting Started with SQL
- What is SQL?
- Setting Up a Database
- Basic SQL Commands
3. Working with Databases
- Creating Databases and Tables
- Inserting, Updating, and Deleting Data
- Querying Data with SELECT
4. Advanced SQL Concepts
- Joins and Subqueries
- Aggregations and Group By
- Indexes and Performance Tips
5. SQL in Action
- Building a Small Database Project
- Real-World SQL Scenarios
, Part 2: Python
6. Introduction to Python
- Python Basics: Variables and Data Types
- Setting Up Python for Data Engineering
- Essential Python Libraries
7. Data Manipulation with Python
- Working with Pandas
- Reading and Writing Data
- Data Cleaning and Transformation
8. Automation with Python
- Writing Scripts for Automation
- Scheduling and Running Scripts
9. Python in Action
- Building Data Pipelines
- Real-World Python Scenarios
Part 3: PySpark
10. Introduction to PySpark
- What is PySpark?
- Setting Up PySpark
- Basics of RDDs and DataFrames
11. Data Processing with PySpark
- Loading and Transforming Data
- ETL Processes with PySpark
- Using Spark SQL
12. Advanced PySpark
- Optimization and Performance
- Integrating with Hadoop and Hive
- Streaming Data
