What process ensures data integrity during ingestion into Splunk ES?

Data integrity during ingestion into Splunk Enterprise Security is primarily ensured through data validation checks. This process involves verifying that the incoming data meets specified criteria for completeness and correctness before it is indexed into Splunk. By implementing validation checks, the system can identify malformed data, incomplete logs, or any discrepancies that might affect analysis and reporting later on.

Validation checks can include a variety of mechanisms such as schema validation, ensuring the data follows expected formats, and verifying timestamps, which all help maintain the reliability and accuracy of the data stored in the system. This is crucial for security analysis where complete and correct data is necessary for making informed decisions.

While data compression techniques aim to reduce storage requirements and data encryption methods focus on securing data from unauthorized access, they do not inherently ensure that the data remains accurate or uncorrupted during ingestion. Likewise, data transformation processes may alter the format or structure of data for better usability, but they do not directly address issues of integrity at the point of data entry. Therefore, validation checks are specifically designed to uphold data integrity, making this the correct answer.