Book Image

Improving Your Splunk Skills

By : James D. Miller, Paul R. Johnson, Josh Diakun, Derek Mock
Book Image

Improving Your Splunk Skills

By: James D. Miller, Paul R. Johnson, Josh Diakun, Derek Mock

Overview of this book

Splunk makes it easy for you to take control of your data and drive your business with the cutting edge of operational intelligence and business analytics. Through this Learning Path, you'll implement new services and utilize them to quickly and efficiently process machine-generated big data. You'll begin with an introduction to the new features, improvements, and offerings of Splunk 7. You'll learn to efficiently use wildcards and modify your search to make it faster. You'll learn how to enhance your applications by using XML dashboards and configuring and extending Splunk. You'll also find step-by-step demonstrations that'll walk you through building an operational intelligence application. As you progress, you'll explore data models and pivots to extend your intelligence capabilities. By the end of this Learning Path, you'll have the skills and confidence to implement various Splunk services in your projects. This Learning Path includes content from the following Packt products: Implementing Splunk 7 - Third Edition by James Miller Splunk Operational Intelligence Cookbook - Third Edition by Paul R Johnson, Josh Diakun, et al
Table of Contents (21 chapters)
Title Page

What is a data model?

The Splunk product documentation (2015-2017) defines a data model as:

"a hierarchically structured, search-time mapping of semantic knowledge about one or more datasets (that encode the domain knowledge necessary to generate specialized searches of those datasets) so that Splunk can use these specialized searches to generate reports and charts for pivot users."

Data models enable you to create Splunk reports and dashboards without having to develop Splunk searches (required to create those reports and dashboards), and can play a big part in Splunk app development. You can create your own data models, but before you do, you should review the data models that your organization may have already developed. Typically, data models are designed by those that understand the specifics around the format, the semantics of certain data, and the manner in which...