Flows and Analytics

flows and analytics are two data processing features in litmus edge that serve different use cases flows is a low code, node red https //nodered org/ based editor for building custom data pipelines analytics provides prebuilt processor functions for common analytical and statistical tasks this page compares both features to help you choose the right one for your requirements see flows manager docid\ jghnqyhxbik8x2nhh5vte and analytics docid 8aloe 5 c9ubqjsw0ppcx for detailed feature documentation flows and analytics compared the following table compares the capabilities of both features feature flows analytics out of the box setup no requires json https //www json org/json en html knowledge all functions must be manually configured yes no coding knowledge required predefined functions are ready to use canvas data preview yes use the debug node to view output yes click the view icon on a processor output publishing yes use the datahub publish node yes use the datahub publish output function pipeline setup no flows must be manually configured yes select an input, processor, and output function customization yes fully customizable to your requirements no predefined functions have limited customization options multi format data parsing yes parser nodes support csv, xml, and yaml no dashboard creation yes create and customize flow dashboards no email and sms alerts yes use the email and twilio out nodes no flows flows is a low code, node red based flow editor for building customized data processing pipelines use flows for complex workflows that require custom logic, multi source data integration, or data format transformation building and maintaining flows requires familiarity with json and node red the flows canvas lets you connect the following processing nodes visually in a browser datahub subscribe and publish inject debug trigger execute json parser read file when to use flows use flows when your workflow requires automated manufacturing sequences flows controls the sequence of operations, adjusts settings, routes materials, and changes schedules based on real time data custom data processing algorithms for specialized equipment, flows can analyze sensor data to optimize usage, predict maintenance needs, and prevent failures for additional guides and user scenarios, see flows guides docid\ ccnpmwlj32yt95tvrdhj3 limitations consider these limitations before choosing flows json and node red knowledge required syntax errors in json configuration can cause flow malfunctions and affect the reliability of your manufacturing operations scaling complexity as the number and complexity of flows increase, managing them becomes more demanding, particularly in large deployments where thousands of sensors and devices generate data continuously analytics analytics provides prebuilt mathematical and statistical processor functions for industrial data analysis use analytics to analyze and visualize industrial data without writing custom logic or learning node red to set up a pipeline, select an input, apply a processor, and configure the output litmus edge analytics includes the following processor functions anomaly detection arima filter feature extraction linear prediction normalization statistical prediction xmr chart when to use analytics use analytics when your workflow requires routine performance monitoring analytics tracks key performance indicators (kpis) such as production output, operational efficiency, and machine uptime and presents data in configurable visual formats predictive maintenance analytics identifies patterns in historical and real time data to predict machine or component failures and support proactive maintenance scheduling for additional guides and user scenarios, see analytics guides docid\ xrlqsbhj0 rdauedlzy54 limitations consider these limitations before choosing analytics limited customizability analytics works with predefined functions and is not suited to workflows that require logic outside the available processor types not designed for complex datasets for datasets that require in depth pattern recognition or multi variable correlation analysis, flows provides the customization that analytics cannot