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What is a possible reason for performance issues after loading 2 million customer records in Salesforce?

  1. Data storage is nearing the limit.

  2. Salesforce is not designed to manage millions of records.

  3. Data skew.

  4. Person Account records are not fully indexed.

The correct answer is: Data skew.

Data skew refers to an uneven distribution of data across records, which can lead to performance issues, particularly during operations involving relationships and lookups. When there is data skew, certain records may have a significantly higher number of related child records than others. For example, if a single account has a disproportionate number of related contacts, this can affect the speed and performance of queries and reports involving those records. In situations involving large data sets, such as loading 2 million customer records, if there is significant data skew present, it can lead to inefficient querying processes, greater load times, and increased resource consumption on the Salesforce platform. This challenge becomes more pronounced when performing operations that attempt to access or aggregate data from multiple records that are not evenly balanced, ultimately leading to performance degradation. Recognizing data skew as a factor allows Salesforce administrators and developers to take proactive measures, such as optimizing data architecture, implementing proper indexing strategies, or reshaping data relationships to reduce the heavy reliance on overloaded records.