Western Governors University (WGU) MGMT6010 C207 Data Driven Decision Making Practice Exam

The process of data cleaning primarily involves the preparation and correction of data to improve its quality for analysis, which includes activities such as identifying and eliminating duplicate records. Duplicates can lead to skewed results and inaccurate insights; therefore, removing them is a crucial step in ensuring the integrity of the data set.

While enhancing data visuals is important in the context of data presentation and reporting, it is not part of the data cleaning process itself. Storing data efficiently, on the other hand, pertains to the management of data rather than its quality. Hence, focusing on eliminating duplicates accurately captures the essence of data cleaning as it targets the need for accurate and reliable data for decision making.

Combining this with enhancing data visuals does not fully encapsulate the fundamental goals of data cleaning, which specifically aim to rectify and improve the raw data itself rather than its presentation or storage. Thus, the best option focuses solely on the essential aspect of eliminating duplicates.