Course details

Data Silos, Lakes, & Streams: Sources, Visualizations, & ETL Operations

Data Silos, Lakes, & Streams: Sources, Visualizations, & ETL Operations


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Traditional data warehousing is transitioning to be more cloud-based and this can be a key area that must be mastered for data science. In this course, you will discover how to configure Glue crawlers to work with different data stores on AWS. Examine how to visualize the data stored in the data lake with AWS QuickSight and how to perform ETL operations on the data using Glue scripts.



Expected Duration (hours)
1.5

Lesson Objectives

Data Silos, Lakes, & Streams: Sources, Visualizations, & ETL Operations

  • configure a Redshift cluster to store data
  • load data into a Redshift cluster from S3 buckets
  • configure a JDBC connection on Glue to the Redshift cluster
  • crawl data on a Redshift cluster using a Glue crawler
  • crawl data stored in a DynamoDB table
  • configure the Amazon QuickSight business intelligence tool to visualize data
  • build charts and dashboards in QuickSight
  • define a job in Glue to perform ETL operations
  • run ETL scripts using Glue
  • perform ETL operations in Glue to backup data originally stored in Redshift
  • perform ETL operations in Glue to backup data originally stored in DynamoDB
  • recall how to use AWS services for visualizations and ETL
  • Course Number:
    it_dsdslsdj_03_enus

    Expertise Level
    Expert