Data Lake Sources Visualizations & ETL Operations

This course discusses the transition of data warehousing to cloud-based solutions using the AWS (Amazon Web Services) cloud platform. You will explore Amazon Redshift a fully managed petabyte-scale data warehouse service which forms part of the larger AWS cloud-computing platform. The 12-video course demonstrates how to create and configure an Amazon Redshift cluster; to load data into it from an S3 (simple storage service) bucket; and configure a Glue crawler for stored data. This course examines how to visualize the data stored in the data lake and how to perform ETL (extract transform load) operations on the data using Glue scripts. You will work with the DynamoDB a NoSQL database service that supports key-value and document data structures. You will learn how to use AWS QuickSight a high-performance business intelligence service which integrates seamlessly with Glue tables by using the Amazon Athena Query Service. Finally you will configure jobs to run extract transform and load operations on data stored in our data lake.