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Using Data Stores in AWS

中級スキルレベル

更新日 2026/04

Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.

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AWSCloud

3時間

11 ビデオ

44 演習

3,000 XP

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コース説明

Master the essential AWS data services that power modern applications. In this hands-on course, you'll learn when and why to use DynamoDB, S3, ElastiCache, and OpenSearch by matching each service to real-world access patterns and consistency requirements. You'll design scalable DynamoDB tables with high-cardinality partition keys, perform CRUD operations, and compare Query vs Scan to optimize performance and cost. On the S3 side, you'll implement lifecycle policies to automatically transition data through storage classes and use versioning to protect against accidental deletion. The course wraps up with securing sensitive data end-to-end — classifying PII and PHI, managing secrets with Secrets Manager and Parameter Store, applying data masking techniques, and implementing multi-tenant isolation using IAM condition keys. By the end, you'll be able to choose, build with, and secure AWS data stores for production applications.

前提条件

Intermediate Python Introduction to AWS Boto in Python Introduction to Shell

1

Choosing the Right AWS Data Store

Learn when and why to use DynamoDB, S3, ElastiCache, and OpenSearch. Explore data access patterns, consistency models, lifecycle management, and caching strategies to make informed storage decisions for your applications.

Introduction to Data Stores in AWS

Match data stores to use cases

Explore AWS data services in Console

Compare data store characteristics

Data access patterns and consistency models

Match consistency models to scenarios

Configure DynamoDB read consistency

Analyze access patterns

Data lifecycle management and caching strategies

Match lifecycle strategies to scenarios

Choosing lifecycle policies for data types

Identify caching opportunities

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2

Building with DynamoDB and S3

Go hands-on with AWS's two most essential data services. Design scalable DynamoDB tables, master CRUD operations and indexes, and optimize S3 with storage classes, versioning, lifecycle policies, and replication

Introduction to Amazon DynamoDB

Identify partition key cardinality

Design DynamoDB table with partition key

Design table with composite primary key

DynamoDB CRUD operations and Query vs Scan

Choosing between Query and Scan operations

Understanding PutItem operations in DynamoDB

Preventing race conditions with conditions

DynamoDB indexes, streams, and optimization

Understanding differences between GSI and LSI

Choosing the right GSI design for email lookups

Designing tables with Local Secondary Indexes

S3 deep dive: storage, versioning, and replication

Selecting optimal S3 storage classes

Implementing automatic storage class transitions

Protecting data with S3 versioning

チャプターを開始

3

Securing and Isolating Sensitive Data

Protect application data end-to-end. Classify PII and PHI, encrypt with KMS, manage secrets with Secrets Manager and Parameter Store, sanitize logs, and implement multi-tenant isolation using IAM condition keys.

Data classification, encryption, and AWS KMS

Identifying PII and PHI in application data

AWS vs customer security responsibilities

When to use different encryption types

AWS Secrets Manager and Parameter Store

Selecting the right service for secret management

Understanding how applications access secrets

Understanding automatic credential rotation

Data sanitization and masking

Classifying data by masking technique

Understanding partial masking implementation

Preventing PII exposure in application logs

Multi-tenant data access patterns and IAM policies

Choosing isolation patterns for scenarios

Partition key design for tenant isolation

Understanding IAM condition keys for DynamoDB

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Using Data Stores in AWS

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