AWS Certified Machine Learning – Specialty — Question 158

A retail company wants to combine its customer orders with the product description data from its product catalog. The structure and format of the records in each dataset is different. A data analyst tried to use a spreadsheet to combine the datasets, but the effort resulted in duplicate records and records that were not properly combined. The company needs a solution that it can use to combine similar records from the two datasets and remove any duplicates.
Which solution will meet these requirements?

Answer options

• A. Use an AWS Lambda function to process the data. Use two arrays to compare equal strings in the fields from the two datasets and remove any duplicates.
• B. Create AWS Glue crawlers for reading and populating the AWS Glue Data Catalog. Call the AWS Glue SearchTables API operation to perform a fuzzy- matching search on the two datasets, and cleanse the data accordingly.
• C. Create AWS Glue crawlers for reading and populating the AWS Glue Data Catalog. Use the FindMatches transform to cleanse the data.
• D. Create an AWS Lake Formation custom transform. Run a transformation for matching products from the Lake Formation console to cleanse the data automatically.

Correct answer: C

Explanation

The correct answer is C because AWS Glue's FindMatches transform is specifically designed to identify and merge similar records while eliminating duplicates, which fits the company's needs perfectly. Option A lacks the sophistication required for data cleansing, while B focuses on searching rather than merging, and D does not utilize AWS Glue's tailored capabilities for this specific data cleansing task.