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Splunk SPLK-4001 Exam Syllabus Topics:

Topic	Details
Topic 1	Detectors for Common Use Cases: This section of the exam measures the skills of Monitoring Engineers and focuses on building and troubleshooting detectors for various real-world use cases. It includes creating detectors to monitor populations, prevent alert flapping, track cyclic patterns, handle large-scale monitoring, and ensure visibility in ephemeral infrastructure environments.
Topic 2	Monitor Using Built-in Content: This section of the exam measures the skills of Site Reliability Engineers and focuses on utilizing Splunk built-in content for effective monitoring. It includes interpreting data in charts, subscribing to alerts, and using tools such as the Kubernetes Navigator, Cluster Analyzer, and pre-built dashboards to identify and resolve performance issues in nodes, pods, and containers.
Topic 3	Introduction to Alerting on Metrics with Detectors: This section of the exam measures the skills of Operations Engineers and focuses on setting up and managing metric alerts using detectors. Candidates learn to create detectors from charts, clone and modify them, build standalone detectors, and configure muting rules to manage alert noise and response efficiency.
Topic 4	Metrics Concepts: This section of the exam measures the skills of Monitoring Specialists and covers fundamental metrics concepts including data resolution, rollups, and components of a datapoint. It also examines the Splunk Infrastructure Monitoring (IM) Data Model, different metric types, and the role of metadata in defining and structuring metric data.
Topic 5	Introduction to Visualizing Metrics: This section of the exam measures the skills of Data Visualization Analysts and emphasizes creating, managing, and interpreting charts and dashboards. It includes searching for metrics, visualizing data with different chart types, applying rollups and analytic functions, and effectively understanding metric data within dashboards.
Topic 6	Finding Insights Using Analytics: This section of the exam measures the skills of Data Analysts and covers analytical methods for uncovering insights from metrics. It includes finding total values across sources, combining plots, performing time-based comparisons, analyzing trends through ratios and percentages, and applying analytic functions across moving or calendar time windows.