Monday, February 3, 2020

#AnomalyDetection Free Web App "PERFOMALIST" (v1.0) is online and ready for beta testing


Welcome to PERFOMALIST v1.0 - date-time-stamped data on-line analyser  


Functionality
1. VISUALIZATION. Weekly (Monthly in v2+) data profiling to visualize patterns, anomalies and short term seasonality via IT-Control Charts. (v1.0)
2. ANALYSIS. Anomalies and Change Points Detection in date-time stamped data. (v2+)
INPUTCSV file with timestamp data (time series observations of a dynamic object). 

Sample input data can be downloaded from from the Download Input Data Sample

Data granularityhourly (v1.0); minutely, daily (v2+)

OUTPUT:
- IT-Control Chart (see example below)  (v1.0)
- Data cube with  summarized data (168 rows/weekhours - v1.0)
- List of anomalies and change points (v2+)

Requirement: 
Input data should consist of at least 3 weeks of history as the method requires comparing the last 7 days of data (actual) with at least 2 weeks long learning/reference data set (baseline). 
The size of the history is limited by about 5 years. Unlimited size of input data will be implemented in v.2.

Additional resources:
How to read IT-Control Chart (on-line article)
- On-line class "Performance Anomaly Detection"

Project contributors:
- Anfisa Trubina 



#AnomalyDetection Free Web App "PERFOMALIST" (v1.0) is online and ready for beta testing

Welcome to  PERFOMALIST v1.0   -   date-time-stamped data on-line analyser   Functionality :  1. VISUALIZATION. Weekly (Monthly in ...