AWS Certified Data Analytics Specialty 2021 – Hands-On - (Exercise) DynamoDB

The video tutorial guides viewers through building an order history app using AWS services. It introduces DynamoDB and explains how to set up a table with partition and sort keys. The tutorial covers installing the Boto3 library on an EC2 instance and configuring AWS credentials. A consumer script is used to process data from a Kinesis stream and insert it into DynamoDB. The tutorial concludes with verifying the data insertion and discussing future integration with AWS Lambda.

What is the primary reason for using a custom consumer script instead of AWS Lambda in the initial setup?

• Custom scripts are more efficient than AWS Lambda.

• AWS Lambda is not covered yet in the course.

• Custom scripts are easier to debug.

• AWS Lambda is not compatible with DynamoDB.

Why is a sort key necessary in the DynamoDB table setup?

• To increase the speed of data retrieval.

• To reduce the cost of data storage.

• To provide a unique key for each record.

• To ensure data is stored in alphabetical order.

Which Python version is recommended for use on the EC2 instance?

• Python 2.7

• Python 3.5

• Python 3

• Python 2.6

What is the purpose of the 'boto3' library in the consumer script?

• To create a web interface for the app.

• To connect to AWS services like Kinesis and DynamoDB.

• To manage user authentication.

• To perform data analysis.

How is a unique sort key created for each line item in the data set?

• By using a random number generator.

• By concatenating the invoice number and stock code.

• By using the customer ID.

• By appending a timestamp.

What is the role of the consumer script in the data flow process?

• To delete old data from the DynamoDB table.

• To insert data from the Kinesis stream into DynamoDB.

• To convert data from JSON to CSV format.

• To generate new data for the DynamoDB table.

What future improvement is suggested for the consumer script?

• Replacing it with a more efficient custom script.

• Integrating it with AWS Lambda for better scalability.

• Adding more logging features.

• Using a different programming language.