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This GitHub project provides a series of lab exercises which help users get started using the Redshift platform.
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README.md

Redshift Immersion Day Labs

This GitHub project provides a series of lab exercises which help users get started using the Redshift platform.

Goals

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse solution that uses columnar storage to minimise IO, provides high data compression rates, and offers fast performance. This GitHub project provides a series of lab exercises which help users get started using the Redshift platform. It also helps demonstrate the many features built into the platform.

Labs

# Lab Name Lab Description
1 Creating Redshift Clusters Cluster setup and connectivity with SQL Workbench/J
2 Data Loading Table creation, data load, and table maintenance
3 Table Design & Query Tuning Setting distribution and sort keys, deep copy, explain plans, system table queries
4 Modernize Your Data Warehouse with Amazon Redshift Spectrum Query petabytes of data in your data warehouse and exabytes of data in your S3 data lake, using Redshift Spectrum
5 Amazon Redshift Spectrum Query Tuning Diagnose Redshift Spectrum query performance and optimize by leveraging partitions, optimizing storage, and predicate pushdown.
6 Query Redshift from Amazon RDS PostgreSQL JOIN Amazon Redshift AND Amazon RDS PostgreSQL WITH dblink
7 Amazon Redshift Operations Step through some common operations a Redshift Administrator may have to do to maintain their Redhshift environment including Event Subscriptions, Cluster Encryption, Cross Region Snapshots, and Elastic Resize
8 Querying Nested JSON Query Nested JSON datatypes (array, struct, map) and load nested data types into flattened structures.

License Summary

This sample code is made available under the MIT-0 license. See the LICENSE file.

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