DEA-C01 · Question #307
DEA-C01 Question #307: Real Exam Question with Answer & Explanation
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Question
A manufacturing company uses AWS Glue jobs to process IoT sensor data to generate predictive maintenance models. A data engineer needs to implement automated data quality checks to identify temperature readings that are outside the expected range of -50°C to 150°C. The data quality checks must also identify records that are missing timestamp values. The data engineer needs a solution that requires minimal coding and can automatically flag the specified issues. Which solution will meet these requirements?
Options
- ACreate an AWS Glue DataBrew project to profile the sensor data Define completeness rules for
- BUse AWS Glue's Data Quality rules and machine learning (ML)-based anomaly detection to
- CCreate an AWS Lambda function to scan the sensor data files to validate temperature ranges.
- DCreate an AWS Glue DynamicFrame that uses a custom data quality operator to profile the
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