Splunk Search Expert Fast Start
Upcoming Classes
Online
Instructor-led online training
Location | Feb 2023 | Mar 2023 | Apr 2023 | May 2023 | Jun 2023 | Jul 2023 | Aug 2023 |
---|---|---|---|---|---|---|---|
AMER Eastern Time - Virtual |
Feb 8 – Feb 10 Feb 22 – Feb 24 |
Mar 1 – Mar 3 Mar 29 – Mar 31 |
Apr 19 – Apr 21 | ||||
APAC Singapore - Virtual |
Feb 13 – Feb 15 |
Mar 20 – Mar 22 |
May 1 – May 3 | ||||
AMER Pacific Time - Virtual |
Feb 15 – Feb 17 |
Mar 8 – Mar 10 |
Apr 5 – Apr 7 Apr 26 – Apr 28 | ||||
EMEA UK Time - Virtual |
Mar 6 – Mar 8 |
Apr 17 – Apr 19 | |||||
AMER Central Time - Virtual |
Mar 29 – Mar 31 |

Summary
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)
Description
- Working with Time
- Statistical Processing
- Comparing Values
- Result Modification
- Leveraging Lookups and Subsearches
- Correlation Analysis
Objectives
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