Data Architecture Deep Dive - Design & Implementation

Data Science
  • 12 Videos | 40m 8s
  • Includes Assessment
  • Earns a Badge
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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.

WHAT YOU WILL LEARN

  • 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

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 46s
    UP NEXT
  • Playable
    2. 
    Data Complexity Management Strategies
    4m 23s
  • Locked
    3. 
    Data Modeling Process
    2m 58s
  • Locked
    4. 
    Distributed Data Management
    2m 40s
  • Locked
    5. 
    Partitioning Methods and Criteria
    2m 23s
  • Locked
    6. 
    MongoDB Partitioning
    5m 16s
  • Locked
    7. 
    Hybrid Data Architectures
    2m 57s
  • Locked
    8. 
    Implement Directed Acyclic Graph
    2m 52s
  • Locked
    9. 
    CAP Theorem
    3m 7s
  • Locked
    10. 
    Batch vs. Streaming
    2m 10s
  • Locked
    11. 
    Read and Write Concerns
    2m 22s
  • Locked
    12. 
    Exercise: Implement Serverless Architecture
    2m 13s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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