Possibly wrong order of steps

[Viktorrr]

The question claims the correct answer as:

Step 1: Create a single Amazon Bedrock Data Automation (BDA) project and define multiple category-specific blueprints with descriptions and required fields.

Step 2: Configure an Amazon EventBridge rule to monitor the S3 bucket and trigger an AWS Lambda function when new documents are uploaded.

Step 3: Set up the AWS Lambda function to call InvokeDataAutomationAsync API, allowing Amazon Bedrock Data Automation (BDA) to auto-select the correct blueprint and extract the needed fields.

Shouldn’t it be Step 1, Step 3, and then Step 2? So we create the Lambda function first, and then configure the EventBridge to trigger it.

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A nationwide property management firm manages a broad portfolio of commercial spaces and residential complexes distributed across several metropolitan areas. The organization recently integrated Amazon SageMaker Clarify into the analytics workflow to support ongoing evaluations of bias trends within tenant survey datasets. As the modernization program progresses, leadership aims to streamline the processing of operational documentation across the enterprise.

Each month, thousands of maintenance invoices, pest-control service reports, and landscaping service statements are collected from external providers. These documents arrive in inconsistent PDF format, and each document category contains a unique set of required fields used by auditing and cost-allocation systems. All documents are delivered to an Amazon S3 bucket through the centralized ingestion pipeline. The required solution must automatically determine the document category and extract the appropriate structured fields without reliance on custom servers, manual parsing logic, or format-specific processing scripts.

Select and order the correct steps from the list below to create an automated document categorization and field extraction with minimal operational responsibility. Each step should be selected once or not at all. (Select and order THREE.)

• Use Amazon Rekognition to build a Custom Labels model trained on sample images representing each document category.
• Configure an Amazon EventBridge rule to monitor the S3 bucket and trigger an AWS Lambda function when new documents are uploaded.
• Create three separate Amazon Bedrock Data Automation (BDA) projects, each tied to a different document category with its own blueprint and field definitions.
• Invoke Amazon Textract AnalyzeDocument with query-based extraction to retrieve text and structural elements from the document.
• Create a single Amazon Bedrock Data Automation (BDA) project and define multiple category-specific blueprints with descriptions and required fields.
• Set up the AWS Lambda function to call InvokeDataAutomationAsync API, allowing Amazon Bedrock Data Automation (BDA) to auto-select the correct blueprint and extract the needed fields.

[Lois-TutorialsDojo]

Hello Viktorrr,

Thanks for pointing this out. Your understanding is correct, and we appreciate you taking the time to raise it.

The original order of steps (Step 1 → Step 2 → Step 3) reflects the conceptual workflow: first define the BDA project and blueprints, then conceptually set up the event trigger, and finally execute the extraction via Lambda. From an exam standpoint, this order shows the logical flow of processing documents rather than literal resource creation.

However, in an actual AWS deployment, your understanding is correct: the sequence should be Step 1, Step 3, then Step 2. You first create the BDA project, then create the Lambda function that calls InvokeDataAutomationAsync, and finally configure the EventBridge rule to trigger the Lambda, because EventBridge requires the Lambda to exist beforehand.

We appreciate you highlighting this. We have already flagged the question and will update it to make the wording clearer and better reflect the exam context. Feel free to reach out if you have any follow-up questions.

Regards,

Lois @ Tutorials Dojo