
Databricks Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice, (Paperback)
Key item features
- Comprehensive Certification Guide: This paperback study guide provides in-depth guidance and practice for the Databricks Certified Data Engineer Associate exam, covering all necessary topics.
- Essential Skill Development: Learn to develop ETL pipelines in both batch and streaming modes, orchestrate data workflows, design dashboards, and maintain data governance on the Databricks platform.
- Practical Learning Exercises: The guide includes hands-on exercises to reinforce understanding, from setting up a Databricks workspace to deploying production pipelines.
- Exam Preparation Focus: Features mock tests and detailed insights into the exam content to help candidates prepare thoroughly and ace the certification.
- Expert Author Instruction: Authored by Derar Alhussein, a senior data engineer with extensive Databricks experience and multiple certifications, ensuring expert-led instruction.
- Key Platform Utilization: Master the effective use of the Databricks Platform, Delta Lake, Apache Spark SQL for advanced ETL, and implement data governance with Unity Catalog.
- Publication Details: This 408-page paperback, ISBN 9781098166830, is authored by O'Reilly Media and is scheduled for publication on March 25, 2025.
Specs
- Book formatPaperback
- Fiction/nonfictionNon-Fiction
- GenreComputing & Internet
- Publication dateFebruary, 2025
- Pages408
- Reading levelPreschool
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Product details
Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform.
In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests.
Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks!
You'll learn how to:
- Use the Databricks Platform and Delta Lake effectively
- Perform advanced ETL tasks using Apache Spark SQL
- Design multi-hop architecture to process data incrementally
- Build production pipelines using Delta Live Tables and Databricks Jobs
- Implement data governance using Databricks SQL and Unity Catalog
Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.
- Databricks Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice, (Paperback)
- Author: O'Reilly Media
- ISBN: 9781098166830
- Format: Paperback
- Publication Date: 2025-03-25
- Page Count: 408
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Book format
Fiction/nonfiction
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Publication date
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