---
title: Analytics
slug: litmusedge-v1/product-features/analytics
description: You can use the Analytics module to create and manage analytics flows. Analytics flows enable you to process and analyze data at the edge.
docTags: 
createdAt: 2022-03-30T21:10:36.000Z
---

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. 

:::hint{type="warning"}
**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](https://www.tensorflow.org/guide/saved_model). 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:**

1. Log in to Litmus Edge.
2. From the Navigation panel, select **Analytics**.
   The *Analytics *canvas appears.

::Image[]{src="https://api.archbee.com/api/optimize/SSUUxKZUk9bFTEPNn_6Zo/HZz2JRKNBS0FCLHAc-7Mz_image.png" size="80" width="910" height="416" caption="Analytics canvas" position="center" showCaption="true"}

# 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)