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Splunk: Data Manipulation

Learn how to parse and manipulate data in Splunk.

Task 1: Introduction

Task 2: Scenario Briefing

Task 3: How Splunk Processes Data

Task 4: Exploring Configuration Files

Task 5: Creating a Splunk App

Task 6: Configuring Event Boundaries

Task 7: Parsing Multi-Line Events

Task 8: Masking Sensitive Data

Task 9: Extracting Custom Fields

Task 10: Conclusion

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Splunk: Data Manipulation

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Learn how to parse and manipulate data in Splunk.

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90 min

16,606

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Data processing, parsing, and manipulation in are crucial for extracting meaningful insights and enabling effective analysis of machine-generated data. Correctly parsed data allows Splunk to extract fields and values, making them searchable, structured, and ready for analysis. From a security perspective, these capabilities are particularly valuable in identifying and responding to security threats, investigating incidents, and monitoring system health. This is because well-structured data enables analysts to correlate events across multiple sources, detect anomalies more accurately, and create actionable detections or alerts.

Learning Objectives

  • Understand how Splunk ingests, parses, and normalizes machine data
  • Create and manage core Splunk configuration files to control data
  • Extract, normalize, and mask sensitive or custom fields
  • Apply data manipulation techniques to build accurate search results 

Prerequisites

Answer the questions below

I understand the learning objectives and am ready to manipulate data with Splunk!