본문으로 건너뛰기

Analyzing Ticket Sales Data with Amazon Redshift

Using AWS's Amazon Redshift, we’ll be analyzing ticket sales data.
Filip Schouwenaars
Filip Schouwenaars

무료 계정 만들기

실습 문제하고 트랙하세요.

Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.

함께 코드 따라하기

코드 따라하기 ↗

In this live training, we’ll be analyzing ticket sales data through Amazon Redshift, a data warehouse product that is part of Amazon Web Services.

Even though Redshift’s underlying technology is vastly different from classical relational databases, we can also run queries using SQL. Using DataLab, we will connect to a redshift cluster and start with some initial exploration of the data.

Next, we move on to answering increasingly complex analytics questions using common techniques like joining, grouping, and aggregating the data.

To top it all off, we will create an insightful visualization that shows the highest-grossing events in the dataset. Filip will provide a template workspace for you so you can easily follow along as he’s coding up the model.

Key takeaways

  • Connect to a Redshift cluster, and browse tables with DataLab

  • Run queries against a Redshift cluster with DataLab

  • Perform joins of multiple tables, and grouped aggregate functions to answer increasingly complex questions

주제

관련

튜토리얼

A Complete Guide to DataWarehousing on AWS with Redshift

튜토리얼

DynamoDB to Redshift: Three Methods for Migrating Data