Course details

Data Architecture - Deep Dive: Design & Implementation

Data Architecture - Deep Dive: Design & Implementation


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

This 11-video Skillsoft Aspire course explores the numerous types of data architecture that can be used when working with big data; how to implement strategies by using NoSQL (not only structured query language); CAP theorem (consistency, availability, and partition tolerance); and partitioning to improve performance. Learners examine the core activities essential for data architectures: data security, privacy, integrity, quality, regulatory compliances, and governance. You will learn different methods of partitioning, and the criteria for implementing data partitioning. Next, you will install and explore MongoDB, a cross-platform document-oriented database system, and learn to read and write optimizations in MongoDB. You will learn to identify various important components of hybrid data architecture, and adapting it to your data needs. You will learn how to implement DAG (Directed Acyclic Graph) by using the Elasticsearch search engine. You evaluate your needs to determine whether to implement batch processing or stream processing. This course also covers process implementation by using serverless and Lambda architecture. Finally, you will examine types of data risk when implementing data modeling and design.



Expected Duration (hours)
0.6

Lesson Objectives

Data Architecture - Deep Dive: Design & Implementation

  • Course Overview
  • 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
  • Course Number:
    it_dsfddadj_01_enus

    Expertise Level
    Intermediate