AWS Certified Data Analytics Specialty 2021 – Hands-On - (Exercise) AWS Glue and Athena

This video tutorial demonstrates how to use Amazon Athena and AWS Glue to query data stored in S3. It covers setting up a Glue Crawler to infer a schema from CSV files, configuring the crawler, and running it to create a database in the data catalog. The tutorial also explains how to edit the schema and partitions, and finally, how to use Athena to perform SQL-like queries on the structured data. The process allows users to treat raw CSV data in S3 as a database, enabling efficient data analysis.

What is the primary purpose of using Amazon Athena in conjunction with AWS Glue?

• To store large amounts of data

• To query data stored in S3 as if it were a SQL database

• To manage user access to AWS resources

• To create visualizations of data

What is the first step in setting up an AWS Glue Crawler?

• Setting up a schedule

• Creating a new crawler and giving it a name

• Adding a data source

• Creating a new IAM role

Which data source is used in the tutorial for the AWS Glue Crawler?

• JDBC

• DynamoDB

• MongoDB

• S3

What is the purpose of creating an IAM role in the AWS Glue setup?

• To schedule the crawler

• To provide access to the data source

• To encrypt the data

• To create a new database

What is the significance of partitions in the AWS Glue schema?

• They are used for data encryption

• They are used to create visualizations

• They represent different data types

• They correspond to the directory structure in S3

Why is it recommended not to change the inferred data types directly in AWS Glue?

• It can cause data loss

• It can lead to synchronization issues

• It is not supported by AWS

• It requires additional permissions

What must be set up in Amazon Athena before running a query?

• A new crawler

• An output location

• A new database

• A new IAM role

What type of data is being queried in the tutorial using Amazon Athena?

• XML data

• Parquet data

• JSON data

• CSV data

What is the result of the sample query executed in Amazon Athena?

• A list of all orders

• A count of orders from France for a given month

• A summary of all data types

• A visualization of sales trends

What is the main advantage of using AWS Glue and Amazon Athena together?

• They automatically generate data visualizations

• They offer free data storage

• They allow querying of unstructured data as if it were structured

• They provide real-time data processing