• Online, Self-Paced
Course Description

Explore various types of data architecture and implementation of strategies using NoSQL, CAP theorem, and partitioning to improve performance.

Learning Objectives

Data Architecture - Deep Dive: Design & Implementation

  • describe data complexity management strategies
  • recognize data modeling techniques and describe data modeling processes
  • list prominent distributed data models and their associative implementation benefits
  • describe data partitioning methods and data partitioning implementation criteria
  • install MongoDB and implement data partitioning using MongoDB
  • identify important components of a hybrid data architecture
  • demonstrate how to implement directed acyclic graphs using Elasticsearch
  • describe CAP theorems and their implementation approaches
  • compare the differences between batch and streaming data
  • recognize the read and write optimizations in MongoDB
  • implement serverless architecture with Lambda and data partitioning using MongoDB

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.