Scalable Data Architectures: Getting Started

Data Architecture    |    Beginner
  • 8 videos | 52m 26s
  • Includes Assessment
  • Earns a Badge
Rating 4.6 of 44 users Rating 4.6 of 44 users (44)
Explore theoretical foundations of the need for and characteristics of scalable data architectures in this 8-video course. Learn to use data warehouses to store, process, and analyze big data. Key concepts covered here include how to recognize the need to scale architectures to keep up with needs for storage and processing of big data; how to identify characteristics of data warehouses ideally suiting them to tasks of big data analysis and processing; and how to distinguish between relational databases and data warehouses. Next, learn to recognize specific characteristics of systems meant for online transaction processing and online analytical processing, and how data warehouses are an example of online analytical processing (OLAP) systems. Then, learn to identify various components of data warehouses enabling them to work with varied sources, extract and transform big data, and generate reports of analysis operations efficiently. Finally, study features of Amazon Redshift enabling big data to be processed at scale; features of data warehouses, contrasted with those of relational databases; and two options available to scale compute capacity.

WHAT YOU WILL LEARN

  • Recognize the need to scale architectures to keep up with the needs for storage and processing of big data
    Identify the characteristics of data warehouses that make them ideally suited to the task of big data analysis and processing
    Distinguish between relational databases and data warehouses
    Recognize the specific characteristics of systems meant for online transaction processing and online analytical processing and how data warehouses are an example of olap systems
  • Identify the various components of data warehouses that enable them to work with varied sources, extract and transform big data, and generate reports of analysis operations efficiently
    Recall the features of amazon redshift that enable big data to be processed at scale
    List the features of data warehouses and contrast them with those of relational databases, and contrast the two options available to scale compute capacity

IN THIS COURSE

  • 2m 37s
  • 9m 11s
    Upon completion of this video, you will be able to recognize the need to scale architectures to keep up with the needs for storage and processing of big data. FREE ACCESS
  • Locked
    3.  Introducing Data Warehouses
    4m 53s
    During this video, you will learn how to identify the characteristics of data warehouses that make them more suitable for big data analysis and processing. FREE ACCESS
  • Locked
    4.  Contrasting Warehouses with Relational Databases
    8m 14s
    During this video, you will learn how to distinguish between relational databases and data warehouses. FREE ACCESS
  • Locked
    5.  Data Warehouses for Analytical Processing
    9m 35s
    Upon completion of this video, you will be able to recognize the specific characteristics of systems meant for online transaction processing and online analytical processing, and how data warehouses are an example of OLAP systems. FREE ACCESS
  • Locked
    6.  Data Warehouse Architectural Components
    6m 6s
    Learn how to identify the various components of data warehouses that enable them to work with varied sources, extract and transform big data, and generate reports of analysis operations efficiently. FREE ACCESS
  • Locked
    7.  Amazon Redshift - A Data Warehouse on the Cloud
    5m 10s
    Upon completion of this video, you will be able to recall the features of Amazon Redshift that enable big data to be processed at scale. FREE ACCESS
  • Locked
    8.  Exercise: Scalable Data Architectures
    6m 40s
    Upon completion of this video, you will be able to list the features of data warehouses and contrast them with those of relational databases. You will also be able to contrast the two options available to scale compute capacity. FREE ACCESS

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