What process comes after data ingestion in the data pipeline of Splunk?

After data ingestion in the Splunk data pipeline, the process that follows is data analytics. Once data has been ingested and indexed in Splunk, it can be analyzed in real time to extract valuable insights. This analysis includes searching through the ingested data, applying various statistical methods, generating reports, and visualizing data through dashboards and charts.

Performing data analytics allows users to derive meaningful information from the data. This process can involve running searches, employing machine learning techniques, and creating alerts based on the patterns found in the data. Given its capabilities, Splunk is primarily used to help organizations monitor, analyze, and visualize their operational data, making data analytics a crucial step in the workflow after ingestion.

In contrast, while data deletion, data export, and data archiving have their respective roles in data management, they do not directly follow data ingestion in terms of processing the data for insights. Data deletion is typically a maintenance task, data export is about transferring data outside of Splunk for external use, and data archiving is generally focused on long-term storage strategies for data that is not frequently accessed. Thus, the focus on analytics after ingestion is foundational for leveraging Splunk's full potential in deriving insights from data.