Data Management Last updated Save as PDF Share Share Tweet Share AAdding a heavy forwarder to Splunk Cloud PlatformAlerting on missing source typesAlerting on source type volume with machine learningCChecking the quality of your data sourcesConfiguring new source typesGGetting to know your dataIImproving data pipeline processing in Splunk EnterpriseMMerging common values from separate fieldsNNormalizing values to a common field name with the Common Information Model (CIM)OOrganizing machine learning data flowsPPreparing data for use with the Machine Learning Toolkit (MLTK)RReceiving and storing queued time series dataReducing event delay in Splunk EnterpriseReducing low-value data ingestion to improve license usageSSampling data with ingest actions for data reductionSending Splunk Observability events as Alert ActionsSetting data retention rules in Splunk Cloud PlatformSolving data quality issuesUUsing ingest actions in Splunk EnterpriseUsing ingest actions with source types that are renamed with props and transformsUsing OpenTelemetry to get data into Splunk Cloud PlatformUsing Table Views to prepare data without SPLWWriting better searches with the Common Information Model
