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