Читать книгу Official Google Cloud Certified Professional Data Engineer Study Guide - Dan Sullivan - Страница 8

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 Essentials Review Questions

16  Chapter 9 Deploying Machine Learning Pipelines Structure of ML Pipelines GCP Options for Deploying Machine Learning Pipeline Exam Essentials Review Questions

17  Chapter 10 Choosing Training and Serving Infrastructure Hardware Accelerators Distributed and Single Machine Infrastructure Edge Computing with GCP Exam Essentials Review Questions

18  Chapter 11 Measuring, Monitoring, and Troubleshooting Machine Learning Models Three Types of Machine Learning Algorithms Deep Learning Engineering Machine Learning Models Common Sources of Error in Machine Learning Models Exam Essentials Review Questions

19  Chapter 12 Leveraging Prebuilt Models as a Service Sight Conversation Language Structured Data Exam Essentials Review Questions

20  Appendix Answers to Review Questions Chapter 1: Selecting Appropriate Storage Technologies Chapter 2: Building and Operationalizing Storage Systems Chapter 3: Designing Data Pipelines Chapter 4: Designing a Data Processing Solution Chapter 5: Building and Operationalizing Processing Infrastructure Chapter 6: Designing for Security and Compliance Chapter 7: Designing Databases for Reliability, Scalability, and Availability Chapter 8: Understanding Data Operations for Flexibility and Portability Chapter 9: Deploying Machine Learning Pipelines Chapter 10: Choosing Training and Serving Infrastructure Chapter 11: Measuring, Monitoring, and Troubleshooting Machine Learning Models Chapter 12: Leveraging Prebuilt Models as a Service

21  Index

22  End User License Agreement