About advanced statistics
You can use the stats
and eval
commands, and how to create sparkline charts. See calculate basic statistics.
Additionally, you can detect anomalies in your data. This might include finding outliers to identify anomalies or spikes in your data. See About anomaly detection and Detecting anomalies.
You might want to remove outliers that unnecessarily skew your calculations or the way your charts plot the data. See Finding and removing outliers
You can detect patterns in your data, grouping events based on how similar the events are to each other. See Detecting patterns.
If there are patterns and correlations to events that you monitor, you can use them to predict future activity. With this knowledge, you can proactively send alerts based on thresholds and perform "what-if" analyses to compare various scenarios. See About time series forecasting and Machine Learning Toolkit.
See also
Add sparklines to search results | Commands for advanced statistics |
This documentation applies to the following versions of Splunk® Enterprise: 7.0.0, 7.0.1, 7.0.2, 7.0.3, 7.0.4, 7.0.5, 7.0.6, 7.0.7, 7.0.8, 7.0.9, 7.0.10, 7.0.11, 7.0.13, 7.1.0, 7.1.1, 7.1.2, 7.1.3, 7.1.4, 7.1.5, 7.1.6, 7.1.7, 7.1.8, 7.1.9, 7.1.10, 7.2.0, 7.2.1, 7.2.2, 7.2.3, 7.2.4, 7.2.5, 7.2.6, 7.2.7, 7.2.8, 7.2.9, 7.2.10, 7.3.0, 7.3.1, 7.3.2, 7.3.3, 7.3.4, 7.3.5, 7.3.6, 7.3.7, 7.3.8, 7.3.9, 8.0.0, 8.0.1, 8.0.2, 8.0.3, 8.0.4, 8.0.5, 8.0.6, 8.0.7, 8.0.8, 8.0.9, 8.0.10, 8.1.0, 8.1.1, 8.1.2, 8.1.3, 8.1.4, 8.1.5, 8.1.6, 8.1.7, 8.1.8, 8.1.9, 8.1.11, 8.2.0, 8.2.1, 8.2.2, 8.2.3, 8.2.4, 8.2.5, 8.2.6, 8.2.7, 8.2.8, 8.2.9, 8.2.10, 8.2.11, 8.2.12, 9.0.0, 9.0.1, 9.0.2, 9.0.3, 9.0.4, 9.0.5, 9.0.6, 9.0.7, 9.0.8, 9.0.9, 9.0.10, 9.1.0, 9.1.1, 9.1.2, 9.1.3, 9.1.4, 9.1.5, 9.1.6, 9.1.7, 9.2.0, 9.2.1, 9.2.2, 9.2.3, 9.2.4, 9.3.0, 9.3.1, 9.3.2, 8.1.10, 8.1.12, 8.1.13, 8.1.14
Feedback submitted, thanks!