Details zum E-Book

Data Engineering with Apache Spark, Delta Lake, and Lakehouse. Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way

Data Engineering with Apache Spark, Delta Lake, and Lakehouse. Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way

Manoj Kukreja, Danil Zburivsky

E-book
In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on.
Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way.
By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks.
  • 1. The Story of Data Engineering and Analytics
  • 2. Discovering Storage and Compute Data Lake Architectures
  • 3. Data Engineering on Microsoft Azure
  • 4. Understanding Data Pipelines
  • 5. Data Collection Stage - The Bronze Layer
  • 6. Understanding Delta Lake
  • 7. Data Curation Stage - The Silver Layer
  • 8. Data Aggregation Stage - The Gold Layer
  • 9. Deploying and Monitoring Pipelines in Production
  • 10. Solving Data Engineering Challenges
  • 11. Infrastructure Provisioning
  • 12. Continuous Integration and Deployment (CI/CD) of Data Pipelines
  • Titel: Data Engineering with Apache Spark, Delta Lake, and Lakehouse. Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way
  • Autor: Manoj Kukreja, Danil Zburivsky
  • Originaler Titel: Data Engineering with Apache Spark, Delta Lake, and Lakehouse. Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way
  • ISBN: 9781801074322, 9781801074322
  • Veröffentlichungsdatum: 2021-10-22
  • Format: E-book
  • Artikelkennung: e_2a75
  • Verleger: Packt Publishing