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

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

Audience

Search Experts Knowledge Managers

Prerequisites

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

How Splunk works
Creating Search queries
Knowledge Objects

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