We’ve listed the four most important features of any good data audit log system so you can check whether yours is up to scratch.
A data audit log system tracks who’s changed what, when, and in what way. This information is essential for locating particular interactions, improper activities, and user errors. As such a data audit log system is vital for preserving a system’s security and maintenance.
Key Data Audit Log System Feature One: Separation
A data audit log system must be completely separate from the system under audit. This ensures that the audit log cannot be affected, tampered with, manipulated, or subjected to intentional data loss by those who may wish to hide their actions – namely, the system’s users. If the audit is not separate from the system, there is no way to know whether the data contained in the log is a true record of the facts or not. A non-separated data audit log system is thus essentially redundant.
Key Data Audit Log System Feature Two: Centralisation
If you have more than one system you wish to audit, all should be monitored by a single data audit log system. This means that you won’t need to collate information recorded by separate logs to get a complete and true story. Centralisation saves time when attempting to trace a particular set of activities, and prevents problems to do with contradictory data.
Many organisations have processes that span multiple systems. Collecting the audit data for all of them in one place ensures complete visibility of their entire processes, which is critical when it comes to compliance and support issues.
Key Data Audit Log System Feature Three: Abstraction
Abstraction is the process of converting different types of source system data into a universal format. Since the format of data can vary between source systems, it is important that your data audit log system is able to abstract all source data. Abstraction allows you to search through the entire data set in a uniform fashion. This means you don’t have to ask the same question in numerous ways – depending on the format it was created in, its structure, or the data values themselves – to get the information you need. Abstraction allow a uniform way to access all data regardless of where it originated from.
Key Data Audit Log System Feature Four: Scalability
It is necessary for a data audit log system to maintain historical information for a long period time. This requirement, combined with the fact that audit data is, by definition, more extensive than source data, means that the amount of data stored by the audit log system will grow exponentially. Moreover, if your organisation grows, more data will need to be logged, which will further increase the volume of data stored. The ability for your data audit to scale up and handle large volumes of data is thus fundamental. (Click here to find out more about the importance of scalability).
So long as your data audit log system has all four of these features, you shouldn’t encounter any problems. However missing out even one may cause you a major headache further down the line. Remember, like anything, a data audit system is only worth it if it’s done properly.