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Answer: Use AWS Glue DataBrew to create a new project, select the dataset, and apply data quality rules to identify and resolve inconsistencies.
Option B is the correct answer. To investigate and resolve data consistency issues, you should use AWS Glue DataBrew. By creating a new project, selecting the dataset, and applying data quality rules, you can identify and resolve inconsistencies in the data. Manually inspecting each data field (Option A) is not efficient for large datasets. Ignoring the inconsistencies (Option C) can lead to poor data quality and incorrect analysis. Using a third-party tool (Option D) may not be necessary if AWS Glue DataBrew can meet your data quality needs.
Author: LeetQuiz Editorial Team
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You are working on a data pipeline that ingests data from multiple sources. You have noticed that some of the data fields are empty or contain inconsistent values. How would you investigate and resolve these data consistency issues using AWS Glue DataBrew?
A
Manually inspect each data field and correct the inconsistencies.
B
Use AWS Glue DataBrew to create a new project, select the dataset, and apply data quality rules to identify and resolve inconsistencies.
C
Ignore the inconsistencies and continue processing the data.
D
Use a third-party data quality tool to investigate and resolve the inconsistencies.
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