Official Google Cloud Certified Professional Data Engineer Study Guide. Dan Sullivan

Parham-Thompson has experience with a variety of open source data storage technologies, including MySQL, MongoDB, and Cassandra, as well as a foundation in web development in software-as-a-service (SaaS) environments. Her work in both development and operations in startups and traditional enterprises has led to solid expertise in web-scale data storage and data delivery.

      Valerie has spoken at technical conferences on topics such as database security, performance tuning, and container management. She also often speaks at local meetups and volunteer events.

      Valerie holds a bachelor’s degree from the Kenan Flagler Business School at UNC-Chapel Hill, has certifications in MySQL and MongoDB, and is a Google Certified Professional Cloud Architect. She currently works in the Open Source Database Cluster at Pythian, headquartered in Ottawa, Ontario.

      Follow Valerie’s contributions to technical blogs on Twitter at dataindataout.

      CONTENTS

      1  Cover

      2  Acknowledgments

      3  About the Author

      4  About the Technical Editor

      5  Introduction

      6  Assessment Test

      7  Answers to Assessment Test

      8  Chapter 1 Selecting Appropriate Storage Technologies From Business Requirements to Storage Systems Technical Aspects of Data: Volume, Velocity, Variation, Access, and Security Types of Structure: Structured, Semi-Structured, and Unstructured Schema Design Considerations Exam Essentials Review Questions

      9  Chapter 2 Building and Operationalizing Storage Systems Cloud SQL Cloud Spanner Cloud Bigtable Cloud Firestore BigQuery Cloud Memorystore Cloud Storage Unmanaged Databases Exam Essentials Review Questions

      10  Chapter 3 Designing Data Pipelines Overview of Data Pipelines GCP Pipeline Components Migrating Hadoop and Spark to GCP Exam Essentials Review Questions

      11  Chapter 4 Designing a Data Processing Solution Designing Infrastructure Designing for Distributed Processing Migrating a Data Warehouse Exam Essentials Review Questions

      12  Chapter 5 Building and Operationalizing Processing Infrastructure Provisioning and Adjusting Processing Resources Monitoring Processing Resources Exam Essentials Review Questions

      13  Chapter 6 Designing for Security and Compliance Identity and Access Management with Cloud IAM Using IAM with Storage and Processing Services Data Security Ensuring Privacy with the Data Loss Prevention API Legal Compliance Exam Essentials Review Questions

      14  Chapter 7 Designing Databases for Reliability, Scalability, and Availability Designing Cloud Bigtable Databases for Scalability and Reliability Designing Cloud Spanner Databases for Scalability and Reliability Designing BigQuery Databases for Data Warehousing Exam Essentials Review Questions

      15  Chapter 8 Understanding Data Operations for Flexibility and Portability Cataloging and Discovery with Data Catalog Data Preprocessing with Dataprep Visualizing with Data Studio Exploring Data with Cloud Datalab Orchestrating Workflows with Cloud Composer Exam