Course Description
Explore the loading of data from an external source such as Amazon S3 into a Redshift cluster, as well as the configuration of snapshots and the resizing of clusters. Discover how to use Amazon QuickSight to visualize data.
Learning Objectives
Scalable Data Architectures: Working with Amazon Redshift & QuickSight
- use the AWS console to load datasets to Amazon S3 and then load that data into a table provisioned on a Redshift cluster
- run queries on data in a Redshift cluster and use the query evaluation feature to analyze the query execution metrics
- work with the SQL Workbench client to connect to and query data in a Redshift cluster
- disable automated snapshots for a Redshift cluster and configure a table to be excluded from snapshots
- recover an individual table from the snapshot of an entire cluster
- add more nodes to a Redshift cluster
- scale up each individual node of a Redshift cluster and scale down the number of nodes
- create a security group rule to enable access from Amazon's QuickSight servers to a Redshift cluster
- configure Amazon QuickSight to load data from a table in a Redshift cluster for analysis
- use the QuickSight dashboard to generate a time series plot to visualize sales at a retailer over time
- configure snapshots of Redshift clusters and recall the steps involved in analyzing data in Redshift using QuickSight