Description based upon print version of record.

Cover -- Title Page -- Copyright Page -- Acknowledgments -- About the Author -- About the Technical Editor -- Contents at a Glance -- Contents -- Introduction -- What Does This Book Cover? -- Preparing for the Exam -- Registering for the Exam -- Studying for the Exam -- The Night before the Exam -- During the Exam -- Interactive Online Learning Environment and Test Bank -- Exam Objectives -- Assessment Test -- Chapter 1 History of Analytics and Big Data -- Evolution of Analytics Architecture Over the Years -- The New World Order -- Analytics Pipeline -- Data Sources -- Collection -- Storage

Processing and Analysis -- Visualization, Predictive and Prescriptive Analytics -- The Big Data Reference Architecture -- Data Characteristics: Hot, Warm, and Cold -- Collection/Ingest -- Storage -- Process/Analyze -- Consumption -- Data Lakes and Their Relevance in Analytics -- What Is a Data Lake? -- Building a Data Lake on AWS -- Step 1: Choosing the Right Storage - Amazon S3 Is the Base -- Step 2: Data Ingestion - Moving the Data into the Data Lake -- Step 3: Cleanse, Prep, and Catalog the Data -- Step 4: Secure the Data and Metadata -- Step 5: Make Data Available for Analytics

Using Lake Formation to Build a Data Lake on AWS -- Exam Objectives -- Objective Map -- Assessment Test -- References -- Chapter 2 Data Collection -- Exam Objectives -- AWS IoT -- Common Use Cases for AWS IoT -- How AWS IoT Works -- Amazon Kinesis -- Amazon Kinesis Introduction -- Amazon Kinesis Data Streams -- Amazon Kinesis Data Analytics -- Amazon Kinesis Video Streams -- AWS Glue -- Glue Data Catalog -- Glue Crawlers -- Authoring ETL Jobs -- Executing ETL Jobs -- Change Data Capture with Glue Bookmarks -- Use Cases for AWS Glue -- Amazon SQS -- Amazon Data Migration Service

What Is AWS DMS Anyway? -- What Does AWS DMS Support? -- AWS Data Pipeline -- Pipeline Definition -- Pipeline Schedules -- Task Runner -- Large-Scale Data Transfer Solutions -- AWS Snowcone -- AWS Snowball -- AWS Snowmobile -- AWS Direct Connect -- Summary -- Review Questions -- References -- Exercises & Workshops -- Chapter 3 Data Storage -- Introduction -- Amazon S3 -- Amazon S3 Data Consistency Model -- Data Lake and S3 -- Data Replication in Amazon S3 -- Server Access Logging in Amazon S3 -- Partitioning, Compression, and File Formats on S3 -- Amazon S3 Glacier -- Vault -- Archive

Amazon DynamoDB -- Amazon DynamoDB Data Types -- Amazon DynamoDB Core Concepts -- Read/Write Capacity Mode in DynamoDB -- DynamoDB Auto Scaling and Reserved Capacity -- Read Consistency and Global Tables -- Amazon DynamoDB: Indexing and Partitioning -- Amazon DynamoDB Accelerator -- Amazon DynamoDB Streams -- Amazon DynamoDB Streams - Kinesis Adapter -- Amazon DocumentDB -- Why a Document Database? -- Amazon DocumentDB Overview -- Amazon Document DB Architecture -- Amazon DocumentDB Interfaces -- Graph Databases and Amazon Neptune -- Amazon Neptune Overview -- Amazon Neptune Use Cases

Storage Gateway.

Wiley Frontlist Obook All English 2020