To ignore spaces when joining data from a database and a lakehouse with minimal development, which approach should you take?

• A. Append the queries by using fuzzy matching
• B. Merge the queries by using fuzzy matching
• C. Append the queries by using a lookup table
• D. Merge the queries by using a lookup table

Answer: (B)

Focus on joining two datasets by finding rows that refer to the same entity even when their keys aren’t exactly identical. Using a merge with fuzzy matching lets the system treat similar keys as matches, so spaces and other small differences don’t prevent the join. This gives you the desired result with minimal development because you’re not creating extra mapping tables or writing separate normalization steps. Appending would simply stack rows without aligning them, and a lookup-table approach would require building and maintaining a separate mapping, which adds overhead. So merging the data with fuzzy matching provides the correct balance of accurate joining and low maintenance.