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As a Microsoft Fabric Analytics Engineer Associate, you are working on a project that involves analyzing a large dataset for a retail company. During the initial data exploration phase, you discover that the dataset contains duplicate records. The dataset is critical for generating monthly sales reports and customer insights. The company emphasizes data accuracy and compliance with data protection regulations. Considering these constraints, which of the following approaches would you recommend to identify and resolve issues with duplicate data in the dataset? (Choose the best option.)
A
Automatically delete all duplicate records without any review to save time and resources, assuming that duplicates are errors.
B
Manually review each duplicate record to determine its validity, which ensures accuracy but may not be feasible due to the dataset's size and time constraints.
C
Implement a hybrid approach using automated tools to flag potential duplicates for manual review, considering factors like data source reliability and the context of the data, to balance efficiency and accuracy.
D
Proceed with the analysis without addressing the duplicate records, as they might represent valid transactions or entries, risking the integrity of the reports and insights.