Data models are becoming an essential part of the App developer's toolkit. They help developers design and maintain the "semantic knowledge" of their data. Semantic knowledge can be described as the underlying knowledge of the meaning and assessment of the data that is being consumed. This knowledge is typically known only to subject matter experts, but it can be transferred to the end user in the form of data models. These data models can then be summarized and accelerated as needed with Splunk Enterprise. Data models are also the driving force behind the Pivot feature of Splunk Enterprise. They define how data is related and/or broken down. They are created using searches that are "tiered" into different sections. For example, your root event may be tag=web_logs (which says that you want all web logs, including IIS or Apache), and the second tier may be Errors, which will constrain the "child search" to only web log errors (for example, status = 500). This gives the end user...