Analytics

you can use the analytics module to create and manage analytics flows analytics flows enable you to process and analyze data at the edge a flow includes a series of connected processors, using at least one of the following types input retrieves data from a tag/topic, database, or generator see input processors docid\ dn4l8ext2aetiogw06auk for details function processes the input data using built in kpis (key performance indicators) see key performance indicators docid\ wvpjmqbun9wrvrwytosyt for details statistical functions see statistical functions docid\ jsq5lksygy7rp3mgqkdix for details output writes the function results to a tag/topic or database see output processors docid\ fhcwpw99glts ajdf7wxl for details see create an analytics flow docid\ xnetldw xyrnsnytlp3h and add processors and processor connections docid\ s6dmqkyhmzvjf7sj8 uyw to learn more important you may see the following error message when working with analytics "http failure response for /analytics/v2/version 0 unknown error" if you see this message, disable any ad blockers your browser may have you can build a flow manually by adding processors and then connecting them with one of the following connection types events (individual data source) used for both input/function and function/output connections makes the receiving processor react to each individual data value immediately values (combined data sources) used only for input/function connections makes the function processor wait for values from all of the combined data sources before reacting for example, if the function processor compares values from input processors a and b, it will wait for a value from both a and b before performing the comparison you can also add a flow in a more automated way see create an analytics flow docid\ xnetldw xyrnsnytlp3h for details the analytics module also enables you to use machine learning models for prediction, classification, and anomaly detection you can create and save a model from tensorflow a saved model contains a complete tensorflow program, including weights and computation the analytics ui includes the following panes instances , where you can create and manage processors and flows view the debug panel organize your flows into groups instances table , where you get tabular view of instance flows created models , where you upload and remove models analytics guides review analytics guides docid\ o9ekcxh d9dmhjoaru 2b to see how to leverage different analytics capabilities and functions access analytics ui to access analytics log in to litmus edge from the navigation panel, select analytics the analytics canvas appears next steps analytics guides docid\ o9ekcxh d9dmhjoaru 2b analytics flows and processors docid\ bifprul6fgg7vc9vnezv8 analytics flow groups docid rtueywcdlseuvoa6osjm instances table docid 83ymhofflwbhqifso7rjb machine learning models docid 4nc2jgjuk5hrwy6ztlrt input processors docid\ dn4l8ext2aetiogw06auk output processors docid\ fhcwpw99glts ajdf7wxl statistical functions docid\ jsq5lksygy7rp3mgqkdix key performance indicators docid\ wvpjmqbun9wrvrwytosyt