Splunk data models and the Pivot tool are key features that enable users to generate statistical data and charts without the complexity of the Search Processing Language (SPL). A data model is a hierarchical mapping of data based on search results. It is analogous to the concept of schemas in a relational database. The output of the search queries associated with the data model can be visualized as a set of rows and columns in a spreadsheet. The data is further subdivided by attributes, which are essentially extracted fields that are similar to those discussed in Chapter 2, Bringing in Data. Since data models are essentially rows and columns of data, we can use them to generate a Pivot table to provide a myriad of different, summarized results.
In this chapter, we will learn how to:
Create a data model
Enable acceleration for the data model
Make a Pivot table
Visualize data using area charts, pie charts, and single value with trend sparklines