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Squirro now provides the functionality of setting up a Trend Detection on a Squirro project. Squirro's Trend detection functionality can be used to find outliers in the historical time-series data and get automatic email alerts for unusual behavior/patterns in your data.
Table of Contents
Trend Detection webinar
Trend Detection Tutorial
What is Trend Detection?
The Trend Detection analysis can be used to detect unusual trends in the time series data. In the Squirro context, time series data is generated in the form of the number-of-items per time-unit in a particular project for a particular query. This time series data can be easily observed today with the histogram bins on the search page (see image below). Trend detection analysis aims to find unusually high peaks in this histogram/time-series automatically.
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How to set up Trend Detection?
The Trend Detection service can now be used with the Squirro client. In In order to set up a new trend-detection on an existing projectTrend Detection on a query of interest, one can use the `new_trenddetection` method of the Squirro client to set up the trend detection for a particular query `q` on a project with project-id `project-id`. A valid email-address is required for generating an email-alert when something unusual is detected for a particular query-projectid pair. Parameter `aggregation_interval` controls the discretisation of the time series (`time-unit` parameter above) before initiating the trend-detection analysis. Based on different values of this parameter, a time-series/histogram will look completely different. An example usage can be seen belowuse the Squirro GUI.
| Code Block |
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>>> client.new_trenddetection(
project_id='2sic33jZTi-ifflvQAVcfw',
query='hello world',
name='test name',
email_user='test@squirro.com',
aggregation_interval='1w') |
How to inspect detected Trends?
Once, a new trend-detection analysis has been created, one will receive alert emails every-time the number of items in a particular time window (defined by the time-unit) goes above the automatically computed threshold for that period. Moreover, one can also see the trends detected in the historical data using the `get_trenddetection_labels` method of the Squirro client. No alert email will be generated for these trends detected in the historical data.
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