Official Google Cloud Certified Professional Data Engineer Study Guide. Dan SullivanЧитать онлайн книгу.

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.

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