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SPLK-DMOD - Data Models

Overview

Duration: 3.0 hours

This three-hour course is for knowledge managers who want to learn how to create and accelerate data models. Topics will cover datasets, designing data models, using the Pivot editor, and accelerating data models.

Objectives

Please refer to course overview

Audience

Search Experts Knowledge Managers

Content

Topic 1 – Introducing Data Model Datasets

  • Understand data models
  • Add event, search, and transaction datasets to data models
  • Identify event objects hierarchy and constraints
  • Add fields based on eval expressions to transaction datasets

Topic 2 – Designing Data Models

  • Create a data model
  • Add root and child datasets to a data model
  • Add fields to data models
  • Test a data model
  • Define permissions for a data model
  • Upload/download a data model for backup and sharing

Topic 3 – Creating a Pivot

  • Identify benefits of using Pivot
  • Create and configure a Pivot
  • Visualize a Pivot
  • Save a Pivot
  • Use Instant Pivot
  • Access underlying search for Pivot

Topic 4 – Accelerating Data Model

  • Understand the difference between ad-hoc and persistent data model acceleration
  • Accelerate a data model
  • Describe the role of tsidx files in data model acceleration
  • Describe the role of tsidx files in data model acceleration
  • Review considerations about data model acceleration

Topic 5 – Enriching Data

  • Understand how fields from lookups, calculated fields, field aliases, and field extractions enrich data

Prerequisites

To be successful, students should have a solid understanding of the following:

  • How Splunk works
  • Creating Search queries
  • Knowledge Objects

Certification

Schedule




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