AWS Certified Data Analytics Specialty 2021 - Hands-On! - Kinesis Analytics Costs and RANDOM_CUT_FOREST

The video tutorial covers AWS Kinesis Analytics, focusing on its scalability and cost implications. It discusses security using IAM permissions, the Schema Discovery feature for SQL column identification, and the Random Cut Forest function for anomaly detection. The tutorial emphasizes careful usage due to potential costs and introduces a hands-on example for practical understanding.

What is a key consideration when using AWS Kinesis Analytics in terms of cost?

• It is free for all AWS users.

• It has a fixed monthly cost regardless of usage.

• It is cheaper than all other AWS services.

• It can be expensive, so manage resources carefully.

Which AWS feature allows you to control access to streaming sources and destinations in Kinesis Analytics?

• AWS Shield

• AWS CloudTrail

• IAM Permissions

• AWS Lambda

What is the purpose of the Schema Discovery feature in Kinesis Analytics?

• To analyze and identify column names in incoming data

• To provide cost estimates for analytics jobs

• To automatically scale resources

• To encrypt data streams

What is the Random Cut Forest feature used for in Kinesis Analytics?

• Encrypting data streams

• Detecting anomalies in numeric data columns

• Generating cost reports

• Scaling resources automatically

In the context of Kinesis Analytics, what real-world example was given for using Random Cut Forest?

• Monitoring server performance

• Identifying anomalous subway ridership during an event

• Detecting fraudulent transactions

• Predicting stock market trends