Splunk Power User Fast Start (POWER-U)
placeFrankfurt 16. Mär 2026 bis 19. Mär 2026check_circle Garantierte Durchführung |
placeHamburg 30. Mär 2026 bis 2. Apr 2026 |
placeBerlin 13. Apr 2026 bis 16. Apr 2026 |
placeHamburg 18. Mai 2026 bis 21. Mai 2026 |
placeMünchen 6. Jul 2026 bis 9. Jul 2026 |
computer Online: Online 24. Aug 2026 bis 27. Aug 2026 |
placeHamburg 5. Okt 2026 bis 8. Okt 2026 |
placeBerlin 26. Okt 2026 bis 29. Okt 2026 |
placeMünchen 16. Nov 2026 bis 19. Nov 2026 |
placeHamburg 7. Dez 2026 bis 10. Dez 2026 |
Kursinhalt
- Working with Time (WWT)
- Statistical Processing (SSP)
- Comparing Values (SCV)
- Result Modification (SRM)
- Correlation Analysis (SCLAS)
- Creating Knowledge Objects (CKO)
- Creating Field Extractions (CFE)
- Data Models (SDM)
Voraussetzungen
To be successful, students should have a solid understanding of the following:
- How Splunk works
- How to create basic searching and visualizations
Detaillierter Kursinhalt
Topic 1 – Working 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
- U…
Es wurden noch keine FAQ hinterlegt. Falls Sie Fragen haben oder Unterstützung benötigen, kontaktieren Sie unseren Kundenservice. Wir helfen gerne weiter!
Kursinhalt
- Working with Time (WWT)
- Statistical Processing (SSP)
- Comparing Values (SCV)
- Result Modification (SRM)
- Correlation Analysis (SCLAS)
- Creating Knowledge Objects (CKO)
- Creating Field Extractions (CFE)
- Data Models (SDM)
Voraussetzungen
To be successful, students should have a solid understanding of the following:
- How Splunk works
- How to create basic searching and visualizations
Detaillierter Kursinhalt
Topic 1 – Working 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 – Correlation Analysis
- Calculate Co-Occurrence Between Fields
- Analyze Multiple Datasets
Topic 6 – Intro to Knowledge Objects
- What are Knowledge Objects?
- Knowledge Object Settings
- Managing Knowledge Objects
Topic 7 – Creating Knowledge Objects
- Knowledge Objects and Search-time Operations
- Creating Event Types
- Using Event Type Builder
- Creating Workflow Actions
- Creating Tags and Aliases
- Creating Search Macros
Topic 8 – Creating Field Extractions
- Using the Field Extractor
- Creating Regex Field Extractions
- Creating Delimited Field Extractions
Topic 9 – Data Models
- Introducing Data Model Datasets
- Designing Data Models
- Creating a Pivot
- Accelerating Data Models
Es wurden noch keine FAQ hinterlegt. Falls Sie Fragen haben oder Unterstützung benötigen, kontaktieren Sie unseren Kundenservice. Wir helfen gerne weiter!
