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 DescriptionUltimate 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 Contents1. Fundamentals of Data Engineering2. Mastering Delta Tables in Databricks3. Data Ingestion and Extraction4. Data Transformation and ETL Processes5. Data Quality and Validation6. Data Modeling and Storage7. Data Orchestration and Workflow Management8. Performance Tuning and Optimization9. Scalability and Deployment Considerations10. Data Security and GovernanceLast WordsIndexAbout the AuthorMayank Malhotra's journey in the tech world began as a big data engineer quickly evolving into a versatile data engineering His extensive experience spans various cloud platforms such as AWS Azure and Databricks as well as On-Prem Infrastructure showcasing his adaptability and depth of knowledge. A BTech graduate Mayank's academic foundation laid the groundwork for his successful career.In the realm of data engineering Mayank has tackled a diverse range of projects from data migration and modeling to data transformation and quality validation. His ability to navigate complex data landscapes has not only honed his skills but also made him a sought-after expert in the field. One of his key beliefs Be the senior you needed as a junior reflects his passion for mentoring. He thrives on guiding others sharing insights and discussing new design approaches in data engineering making him a valuable mentor and leader.