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Implementing Splunk 7, Third Edition

You're reading from   Implementing Splunk 7, Third Edition Effective operational intelligence to transform machine-generated data into valuable business insight

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788836289
Length 576 pages
Edition 3rd Edition
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Author (1):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
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Table of Contents (15) Chapters Close

Preface 1. The Splunk Interface FREE CHAPTER 2. Understanding Search 3. Tables, Charts, and Fields 4. Data Models and Pivots 5. Simple XML Dashboards 6. Advanced Search Examples 7. Extending Search 8. Working with Apps 9. Building Advanced Dashboards 10. Summary Indexes and CSV Files 11. Configuring Splunk 12. Advanced Deployments 13. Extending Splunk 14. Machine Learning Toolkit

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 users may expect to work with that data. In building a typical data model, knowledge managers use knowledge object types...

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