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.
- 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