• Online, Self-Paced
Course Description

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.

Learning Objectives

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.

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Data Administration