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
List of Tables
1 Chapter 1Table 1.1Table 1.2Table 1.3Table 1.4Table 1.5Table 1.6Table 1.7
2 Chapter 9Table 9.1
3 Chapter 11Table 11.1Table 11.2Table 11.3
List of Illustrations
1 Chapter 1Figure 1.1 Choosing a storage technology in GCPFigure 1.2 Example graph of friends
2 Chapter 2Figure 2.1 Basic Cloud SQL configurationFigure 2.2 Optional configuration parameters in Cloud SQLFigure 2.3 Configuring Cloud SpannerFigure 2.4 Configuring a Bigtable clusterFigure 2.5 Cost of a three-node Bigtable production clusterFigure 2.6 BigQuery interactive interface with sample query
3 Chapter 3Figure 3.1 A simple directed graphFigure 3.2 A simple cyclic graphFigure 3.3 An example ingestion stage of a data pipelineFigure 3.4 Data pipeline with transformationsFigure 3.5 Example pipeline DAG with storageFigure 3.6 Complete data pipeline from ingestion to analysisFigure 3.7 A stream with sliding and tumbling three windowFigure 3.8 Data pipeline with both
