Data Lake Sources, Visualizations, & ETL Operations
Amazon Web Services 2019
| Expert
- 13 videos | 1h 27m 53s
- Includes Assessment
- Earns a Badge
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.
WHAT YOU WILL LEARN
-
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
IN THIS COURSE
-
2m 3s
-
9m 8sIn this video, you will learn how to configure a Redshift cluster to store data. FREE ACCESS
-
3. Create Tables and Load Data From S37m 38sIn this video, you will learn how to load data into a Redshift cluster from S3 buckets. FREE ACCESS
-
4. Establish a JDBC Connection to Redshift7m 31sIn this video, you will configure a JDBC connection on Glue to connect to the Redshift cluster. FREE ACCESS
-
5. Crawl Redshift Using a JDBC Connection5m 45sIn this video, learn how to crawl data on a Redshift cluster using a Glue crawler. FREE ACCESS
-
6. Crawl DynamoDB7m 53sIn this video, you will learn how to crawl data stored in a DynamoDB table. FREE ACCESS
-
7. Configure QuickSight to Visualize Data4m 33sDuring this video, you will learn how to configure the Amazon QuickSight business intelligence tool to visualize data. FREE ACCESS
-
8. Visualize Data in QuickSight8m 47sDuring this video, you will learn how to build charts and dashboards in Amazon QuickSight. FREE ACCESS
-
9. Configure a Job to Perform Extract, Transform, Load6m 21sIn this video, you will define a job in Glue to perform ETL operations. FREE ACCESS
-
10. Execute an ETL Operation in Glue6m 43sFind out how to run ETL scripts using AWS Glue. FREE ACCESS
-
11. Perform ETL to Back Up Redshift Data in S3 Buckets8m 31sIn this video, learn how to perform ETL operations in Glue to backup data originally stored in Redshift. FREE ACCESS
-
12. Perform ETL to Back Up DynamoDB Data in S3 Buckets7m 48sLearn how to perform ETL operations in Glue to backup data originally stored in DynamoDB. FREE ACCESS
-
13. Exercise: Multiple Sources, Visualizations, and ETL5m 12sAfter completing this video, you will be able to recall how to use AWS services for visualizations and ETL. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.
