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- COURSE
Splunk Search Expert Fast Start (SE-FS)
Price:
Duration:
Certification:
Exam:
Continuing Education Credits:
Learning Credits:
This "Fast Start" course covers over 60 commands and functions and prepares students to be search experts. Students will learn how to effectively utilize time in searches, work with different time zones, use transforming commands and eval functions to calculate statistics, compare field values with eval functions and eval expressions, manipulate output, normalize fields and field values, use lookups and subsearches to enrich results, and correlate and filter data from multiple sources.
This class will take place over three 6-hour days (plus a 1-hour break each day)
Course Content:
- Working with Time (WWT)
- Statistical Processing (SSP)
- Comparing Values (SCV)
- Result Modification (SRM)
- Leveraging Lookups and Subsearches (LLS)
- Correlation Analysis (SCLAS)
Upcoming Class Dates and Times
All Sunset Learning courses are guaranteed to run
Course Outline and Details
Prerequisites
To be successful, students should have a solid understanding of the following:
- How Splunk Works
- Creating Search queries
- Knowledge objects (specifically reports, lookups, and fields)
OR have taken the following:
- Foundation Fast Start OR
- What is Splunk? (Retired), Intro to Splunk (ITS) and [Using Fields (SUF)
Target Audience
Course Objectives
Course Outline
Topic 1 – Working with Time
- Searching with Time
- Formatting Time
- Comparing index Time versus Search Time
- Using Time Commands
- Working with Time Zones
Topic 2 – Statistical Processing
- What is a Data Series?
- Transforming Data
- Manipulating Data with eval
- Formatting Data
Topic 3 – Comparing Values
- Using eval to Compare
- Filtering with where
Topic 4 – Result Modification
- Manipulating Output
- Modifying Results Sets
- Managing Missing Data
- Modifying Field Values
- Normalizing with eval
Topic 5 – Leveraging Lookups and Subsearches
- Using Lookup Commands
- Adding a Subsearch
- Using the return Command
Topic 6 – Correlation Analysis
- Caclulate Co-Occurance Between Fields
- Analyze Multiple Datasets