Answer-first summary for fast verification
Answer: Define data quality rules using AWS Glue DataBrew by creating a new project, selecting the customer feedback records dataset, and specifying rules to identify and filter out irrelevant or duplicate records.
Option C is the correct answer. To ensure the data quality of the customer feedback records dataset, you should define data quality rules using AWS Glue DataBrew. By creating a new project, selecting the dataset, and specifying rules to identify and filter out irrelevant or duplicate records, you can maintain the integrity of the customer feedback data. Manually inspecting each customer feedback record (Option A) is not efficient for large datasets. Writing custom scripts (Option B) can be time-consuming and may not cover all possible irrelevant or duplicate criteria. Ignoring data quality checks (Option D) is not recommended as it can lead to poor data quality and incorrect analysis.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
You are working on a data pipeline that processes data from a marketing company. The data includes customer feedback records with information about customer satisfaction and preferences. You have been tasked with ensuring the data quality of the customer feedback records dataset. Describe the steps you would take to run data quality checks on the customer feedback records dataset and explain how you would define data quality rules to identify and filter out irrelevant or duplicate feedback records.
A
Run data quality checks by manually inspecting each customer feedback record and identifying irrelevant or duplicate records.
B
Use AWS Glue to run data quality checks by writing custom scripts that identify irrelevant or duplicate records based on specific criteria.
C
Define data quality rules using AWS Glue DataBrew by creating a new project, selecting the customer feedback records dataset, and specifying rules to identify and filter out irrelevant or duplicate records.
D
Ignore data quality checks and assume all customer feedback records are relevant and unique.
No comments yet.