Data Modeling for Amazon DocumentDB

To efficiently meet business needs when designing databases, data modeling is critical. In this course, you will learn the fundamental concepts and best practices of modeling your data with Amazon DocumentDB. You will examine three use cases of modeling or structuring your data, and complete small decision-making exercises to address a hypothetical application need.

      •    Course level: Intermediate

      •    Duration: 60 minutes

Activities

This course includes graphics, contextual explanations, short demonstrations, and knowledge checks.

Course objectives

In this course, you will learn to:

      •    Explore data models available for storing data with Amazon DocumentDB.

      •    Explore relationship types and how to use them with data modes.

      •    Explore data normalization and denormalization methods.

      •    Explain the different types of access patterns.

      •    Identify the ideal architecture for addressing hypothetical application needs.

Intended audience

This course is intended for:

      •    Database architects

      •    Database engineers

      •    Database administrators

      •    Developers

Prerequisites

We recommend that attendees of this course have:

      •    Working knowledge of Amazon DocumentDB or have completed Getting Started with Amazon DocumentDB (with MongoDB compatibility)

      •    Working experience with JSON

Course outline

Module 1: Fundamental Concepts

      •    Introduction

      •    Normalized compared to Denormalized

      •    Embedding compared to Referencing

      •    Relationships

      •    Patterns

Module 2: Data Modeling Use Cases

      •    Scenario Introduction

      •    Designing a Product Catalog

      •    Product Inventory Expansion and Review Functionality

      •    Build Your Own Sundae

Module 3: Wrap-Up

      •    Resources