In the previous chapter, we learned about Splunk's new data model and Pivot functionality and how they can be used to further intelligence reporting. In this chapter, we will return to Splunk's SPL, diving deeper and making use of some very powerful search commands to facilitate a better understanding and correlation of event data. You will learn how to create transactions, build subsearches and understand concurrency, leverage field associations, and so on.

Looking at event counts, applying statistics to calculate averages, or finding the top values over time only provide a view of the data limited to one angle. Splunk's SPL contains some very powerful search commands that provide the ability to correlate data from different sources and understand or build relationships between the events. Through the building of relationships between datasets and looking at different angles of the data, you can better understand the impact one event might have over another. Additionally, correlating...