Data Models The Splunk Education single-subject course module, Data Models is for knowledge managers Data Models Creating a Pivot Accelerating Data Models Enriching Data Class Format Instructor-led lecture Data Models- Course Objectives Topic 1 – Introducing Data Model Datasets Understand data models Add event model Add root and child datasets to a data model Add fields to data models Test a data model Define data model acceleration Review considerations about data model acceleration Topic 5 - Enriching Data

accelerate reports and data models, and how to use the tstats command to quickly query data. Model Acceleration Using the tstats Command Class Format Instructor-led lecture with labs. Model Acceleration Understand data model acceleration Accelerate a data model Use the datamodel command to search data models Topic 4 – Using the tstats Command Explore the tstats command Search acceleration summaries with tstats Search data models with tstats Compare tstats and stats Splunk Course Schedules

Explore 8 advanced modules covering search, reporting, correlation, field extractions, and data models Create workflow actions, event types, knowledge objects and data models. Read More Data Models This Splunk training 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

models, and normalizing data with the Common Interface Model (CIM). models Splunk Common Information Model (CIM) Class Format Instructor-led lecture with labs. models which can be used to run the Pivot tool Add value to your event data using lookups Splunk Fundamentals 13 – Creating Data Models Describe the relationship between data models and pivot Identify data model attributes Create a data model Use a data model in pivot Module 14 – Using the Common Information Model

, creating nested macros and macros with event types, and accelerating reports and data models. models and reports with Splunk who have limited exposure to regular expressions. model acceleration. 9: Using Acceleration Options: Data Models and tsidx Files Exploring data models using datamodel command Using data model acceleration Working with tsidx files using the tstats command Splunk Course Schedules

model and different types of metadata. See how you can interact with data using built-in content, search for metrics, find more information Description Define components of the metrics data model Discriminate between types of metadata Interact 1 - Metrics Data Model Define components of the Splunk IM Data Model Metrics, MTS, datapoints Data resolution between types of metadata Use metadata to segment your data Interact with data using the Infrastructure

Read More Data Models This Splunk training 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 accelerate reports and data models, and how to use the tstats command to quickly query data. Participant, Splunk Enterprise Data Administration

with Lookups $500 or 1 credit View Schedule Knowledge Manager Splunk Fundamentals 3 Data Models $500 Read More Data Models This Splunk training 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 accelerate reports and data models, and how to use the tstats command to quickly query data.

transforming commands and visualisations, filtering and formatting results, creating workflow actions and data models, and normalizing data with the CIM. transforming commands and visualisations, filtering and formatting results, creating workflow actions and data models, and normalizing data with the CIM. Participant, Splunk Enterprise Data Administration

Students will learn steps and best practices for planning, data collection and sizing for a distributed collection Forwarders and managing deployments Data comprehension Search considerations Development with Lookups Data Models Splunk Enterprise Cluster Administration Architecting Splunk Enterprise Deployments 5- Data Collection Compare agent-based and agentless data collection methods Discuss data inputs Compare Common Information Model Discuss Data Models and data model design Discuss data enrichment, including

with Lookups Data Models Splunk Enterprise System TAdministration Splunk Enterprise Data Administration input phases Inputs Parsing Indexing Splunk Enterprise Data Administration - Course Objectives Module 1 - Getting Data Into Splunk Provide an overview of Splunk Describe the Splunk distributed model Describe Preview to validate event creation during parsing phase Module 13 - Manipulating Input Data Explore Mask data with SEDCMD and TRANSFORMS Module 14 - Routing Input Data Filter data with Ingest Action rules

aliases and calculated fields, create tags and event types, use macros, create workflow actions, create data models and normalise data with the Common Information Model in either the Splunk Enterprise or Splunk Values Result Modification Correlation Analysis Creating Knowledge Objects Creating Field Extractions Data Models Cert Exam - Splunk Core Certified Power User Splunk Certifications Exam When you’re ready to Participant, Splunk Enterprise Data Administration