What is the main effect of data skew on system performance?

Data skew primarily refers to an uneven distribution of records among different users or groups within a system. This uneven distribution can lead to performance issues, particularly in environments where operations are heavily reliant on specific data sets. When certain users own a disproportionately large number of records, it can create bottlenecks in the system. For instance, if one user tries to perform actions on a massive set of records, it can slow down the process for everyone else, as the system struggles to allocate resources efficiently.

By negatively impacting performance, data skew may lead to longer load times, delays in processing data, and increased chances of system errors or timeouts during peak usage times. This can severely hinder the user experience and the overall effectiveness of the system, especially in a CRM environment where timely access to data is critical.

On the other hand, aspects like operational efficiency, record ownership, and storage volume are not direct consequences of data skew. While a well-balanced distribution of records can promote operational efficiency, data skew typically has the opposite effect, making it a significant concern for system performance.