Ultimate Data Engineering with Databricks

Navigating Databricks with Ease for Unparalleled Data Engineering Insights.

Key Features

? Navigate Databricks with a seamless progression from fundamental principles to advanced engineering techniques.

? Gain hands-on experience with real-world examples, ensuring immediate relevance and practicality.

? Discover expert insights and best practices for refining your data engineering skills and achieving superior results with Databricks.

Book Description

Ultimate Data Engineering with Databricks is a comprehensive handbook meticulously designed for professionals aiming to enhance their data engineering skills through Databricks. Bridging the gap between foundational and advanced knowledge, this book employs a step-by-step approach with detailed explanations suitable for beginners and experienced practitioners alike.

Focused on practical applications, the book employs real-world examples and scenarios to teach how to construct, optimize, and maintain robust data pipelines. Emphasizing immediate applicability, it equips readers to address real data challenges using Databricks effectively. The goal is not just understanding Databricks but mastering it to offer tangible solutions.

Beyond technical skills, the book imparts best practices and expert tips derived from industry experience, aiding readers in avoiding common pitfalls and adopting strategies for optimal data engineering solutions. This book will help you develop the skills needed to make impactful contributions to organizations, enhancing your value as a data engineering professional in today's competitive job market.

What you will learn

? Acquire proficiency in Databricks fundamentals, enabling the construction of efficient data pipelines.

? Design and implement high-performance data solutions for scalability.

? Apply essential best practices for ensuring data integrity in pipelines.

? Explore advanced Databricks features for tackling complex data tasks.

? Learn to optimize data pipelines for streamlined workflows.

Table of Contents

1. Fundamentals of Data Engineering

2. Mastering Delta Tables in Databricks

3. Data Ingestion and Extraction

4. Data Transformation and ETL Processes

5. Data Quality and Validation

6. Data Modeling and Storage

7. Data Orchestration and Workflow Management

8. Performance Tuning and Optimization

9. Scalability and Deployment Considerations

10. Data Security and Governance

Last Words

Index