Course Description
Explore a theoretical foundation on the need for and the characteristics of scalable data architectures. Using data warehouses to store, process, and analyze big data is also covered.
Learning Objectives
Scalable Data Architectures: Introduction
- 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