2019), NoSQL for Mere Mortals (Addison-Wesley Professional, 2015), and several LinkedIn Learning courses on databases, data science, and machine learning. Dan has certifications from Google and AWS, along with a Ph.D. in genetics and computational biology from Virginia Tech.
About the Technical Editor
Valerie 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
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
