OAC Expert Certification Practice Exam 2025 – Complete Test Prep

Creating a new curated Data Set from several existing Data Sets typically involves combining various sources of data into a cohesive whole that retains relevant information while ensuring that the resultant Data Set meets specific requirements or criteria. Merging columns is an effective way to achieve this because it allows you to integrate different attributes or fields from the existing Data Sets into a unified format.

When merging columns, you can specify how to align the data from different sources, which can include matching rows based on a key attribute. This is particularly important when working with heterogeneous data sources, as it enables you to gather all pertinent information into a single Data Set that is both comprehensive and useful for analysis. Merging helps in eliminating duplication and ensures that the data is structured appropriately for further processing or reporting.

In contrast, filtering data is generally focused on narrowing down the data set based on specific conditions rather than synthesizing multiple datasets into a new one. Aggregating data involves compiling data into summary statistics or groupings, which is useful for analysis but does not directly create a new dataset by combining multiple existing datasets. Adding data directly typically refers to appending new records to a dataset rather than merging or synthesizing existing datasets into a new structure.