The GCP Professional Data Engineer certification validates the fundamental knowledge required to perform data engineering tasks and use GCP services to enhance data engineering processes and further your career in the data engineering/architecting field. This book is a best-in-class study guide that fully covers the GCP Professional Data Engineer exam objectives and helps you pass the exam first time.
Complete with clear explanations, chapter review questions, realistic mock exams, and pragmatic solutions, this guide will help you master the core exam concepts and build the understanding you need to go into the exam with the skills and confidence to get the best result you can.
With the help of relevant examples, you'll learn fundamental data engineering concepts such as data warehousing and data security. As you progress, you'll delve into the important domains of the exam, including data pipelining, data migration, and data processing.
Unlike other study guides, this book contains logical reasoning behind the choice of correct answers based in scenarios and provide you with excellent tips regarding the optimal use of each service, and gives you everything you need to pass the exam and enhance your prospects in the data engineering field.

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Spis treści

Google Cloud Certified Professional Data Engineer Certification Guide. Get certified and develop expert-level data engineering skills with Google Cloud Platform eBook -- spis treści

• 1. Storing Data – Service Selection
• 2. Storing Data – Data Warehousing
• 3. Storing Data – Data Lakes
• 4. Storing Data – Data Mesh
• 5. Data Preparation and Analysis – Data Visualization
• 6. Data Preparation and Analysis – Data Sharing
• 7. Data Preparation and Analysis – Data Exploration and Analysis
• 8. Data Processing Design – Security and Compliance
• 9. Data Processing Design – Reliability and Fidelity
• 10. Data Processing Design – Flexibility and Portability
• 11. Data Processing Design – Data Migrations
• 12. Data Engineering and Processing – Planning Pipelines
• 13. Data Engineering and Processing – Building Pipelines
• 14. Data Engineering and Processing – Pipeline Operations
• 15. Maintenance and Automation – Resource Usage and Cost Optimization
• 16. Maintenance and Automation – Automating and Backing Up Processes