Course details

Scalable Data Architectures: Working with Amazon Redshift & QuickSight

Scalable Data Architectures: Working with Amazon Redshift & QuickSight


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/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.



Expected Duration (hours)
1.3

Lesson 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
  • Course Number:
    it_dssdarcdj_03_enus

    Expertise Level
    Beginner