What is the first step a data analyst should take to load sensitive data from DynamoDB into Amazon Redshift securely?

The most effective first step for securely loading sensitive data from DynamoDB into Amazon Redshift is to use AWS Lambda to process DynamoDB streams. This approach allows for a serverless way to react to changes in your DynamoDB tables, ensuring that any data handling occurs in real time and securely.

Using a Lambda function offers a controlled environment for accessing data. It can integrate tightly with both DynamoDB and Redshift, allowing you to extract, transform, and load (ETL) data efficiently. Furthermore, Lambda can be configured to access only the resources necessary for the task at hand, minimizing exposure and enhancing security.

While options like using IAM roles and encrypting data with AWS KMS are important for overall security and access control, they are supplementary steps that enhance security rather than being the initial action for loading data. An unprotected S3 bucket should be avoided for sensitive data storage as it poses significant security risks.