Scala & Spark-Master Big Data with Scala and Spark - Creating S3 Bucket

This video tutorial guides viewers through setting up an ETL pipeline using AWS services. It begins with an introduction to the ETL process, focusing on data migration from S3 to RDS. The tutorial then provides detailed steps for creating an AWS account and accessing the AWS console. It explains how to set up an S3 bucket, including configuring public access, and demonstrates uploading a CSV file to the bucket. The video concludes with a summary of the first ETL step and a preview of the next video in the series.

What is the primary purpose of the ETL pipeline discussed in the video?

• To develop a mobile application

• To create a new AWS account

• To migrate data from S3 to RDS

• To perform data analysis on local servers

Which AWS services are used in the ETL pipeline project?

• CloudFront and Route 53

• DynamoDB and SQS

• EC2 and Lambda

• S3 and RDS

What is a key requirement when creating an S3 bucket?

• The bucket must be located in the US region

• The bucket must be private

• The bucket must have versioning enabled

• The bucket name must be unique

Why is public access enabled for the S3 bucket in this project?

• To simplify access for demonstration purposes

• To allow anyone to delete the data

• To ensure data is encrypted

• To reduce storage costs

What file format is uploaded to the S3 bucket in the video?

• TXT

• CSV

• XML

• JSON