A data analyst is joining two tables with different content and one common field.

This question falls under theData Acquisition and Preparationdomain, focusing on combining data from multiple tables. The tables have different content but share a common field, indicating a join operation.

Match the records of the related columns and merge the tables (Option A): This describes a join operation, where records are matched on the common field (e.g., a key like Customer_ID) and the tables are merged, which is the most efficient method.

Create a cluster to facilitate data integration between the tables (Option B): Clustering is a machine learning technique, not a method for joining tables.

Explode both tables to identify unique values and reorder the fields in one table (Option C): Exploding is used in nested data (e.g., JSON arrays), and this approach is overly complex and unnecessary.

Append the values of the matching columns and concatenate the other data fields (Option D): Appending stacks tables vertically, and concatenation applies to text, neither of which is appropriate for joining tables with a common field.

The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as joining tables using a common field.