Splunk is a powerful tool used by businesses and organizations to collect, analyze, and visualize their machine data. The Splunk Certified Developer (SPLK-2001) certification exam is designed to validate the skills and knowledge of individuals who want to become proficient in the development and implementation of Splunk applications. Splunk Certified Developer certification exam is intended for developers who have experience in using Splunk to develop apps and want to take their skills to the next level.
Reference: https://www.splunk.com/pdfs/training/Splunk-Test-Blueprint-Developer-v.1.1.pdf
A true simulation environment
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Concise contents
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Splunk SPLK-2001 is a certification exam designed to validate the knowledge and skills of developers who use Splunk software for data analytics. SPLK-2001 exam is intended for professionals who want to demonstrate their proficiency in developing applications, creating dashboards, and performing advanced searches using Splunk. Splunk Certified Developer certification is recognized globally and provides an edge to the individuals who have it in the job market.
A brief introduction to the course
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Splunk SPLK-2001 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Knowledge Objects and Data Models | 20% | - Knowledge objects management
- 1. Lookups and macros
- 2. Saved searches and reports
- Data models
- 1. Data model creation and acceleration
- 2. Pivot and datasets
|
| REST API and Advanced Features | 20% | - Splunk REST API usage
- 1. Data retrieval and automation
- 2. Authentication and endpoints
- Advanced Splunk features
- 1. Alerts and scheduled searches
- 2. Security and role-based access control
|
| Splunk Apps and Add-ons Development | 25% | - Custom search commands and scripts
- 1. Custom search commands development
- 2. Scripted inputs and modular inputs
- App configuration and structure
- 1. App packaging and deployment
- 2. Configuration files (conf files)
|
| Data Inputs and Parsing | 15% | - Event processing
- 1. Event types and tags
- 2. Field extractions and transformations
- Data ingestion and indexing
- 1. Index-time vs search-time processing
- 2. Inputs configuration
|
| SPL Fundamentals and Search Processing | 20% | - Search optimization
- 1. Efficient search strategies
- 2. Time modifiers and performance tuning
- Search Processing Language (SPL) syntax and commands
- 1. Filtering and transforming commands
- 2. Field extraction and manipulation
|