Course Content
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.
Certifications
This course is part of the following Certifications:
Prerequisites
To be successful, students should have a solid understanding of the following:
- How Splunk works
- Creating search queries
- Knowledge objects
Course Objectives
- Introducing Data Model Datasets
- Designing Data Models
- Creating a Pivot
- Accelerating Data Models
Outline: Data Models (SDM)
Topic 1 - Introducing Data Model Datasets
- Understand data models
- Add event, search, and transaction datasets to data models
- Identify event object 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
- Review considerations about data model acceleration
Topic 5 - Enriching Data
- Understand how fields from lookups, calculated fields, field aliases, and field extractions enrich data