A company has difficulty matching customer information between two separate databases. What issue does this exemplify?

The situation described, where a company struggles to match customer information between two separate databases, underscores a data comparability issue. This type of problem arises when data from different sources cannot be reliably compared or integrated due to differences in format, structure, or definitions used within those databases.

For instance, if one database uses “Customer ID” as a unique identifier while another uses “Customer Identification Number,” the inability to match these identifiers can lead to challenges in merging or analyzing data effectively. Data comparability is critical in ensuring that insights drawn from multiple data sources are accurate and actionable.

Recognizing this issue is vital for organizations aiming to enhance data integration and decision-making processes, especially when working with disparate systems or datasets. The other types of issues, such as data accuracy, relevance, and completeness, pertain to different aspects of data management but do not directly address the difficulties faced in matching data between separate databases.