Résumé du cours
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)
Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Pré-requis
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? (WIS), Intro to Splunk (ITS) and Using Fields (SUF)
Objectifs
At the end of the course, you should be able to :
- Search with Time
- Format Time
- Compare Index Time versus Search Time
- Use Time Commands
- Work with Time Zones
- Understand what is Data Series
- Transform Data
- Manipulate Data with eval
- Format Data
- Use eval to Compare
- Filter with where
- Manipulate Output
- Modify Result Sets
- Manage Missing Data
- Modify Field Values
- Normalize with eval
- Use Lookup Commands
- Add a Subsearch
- Use the return Command
- Calculate Co-Occurrence Between Fields
- Analyze Multiple Datasets
Contenu
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
Anglais
Moyens Pédagogiques :