====Analytic Deployment====

When you create a new [[start|Visual Analytic]], you don't only create a simple graph.

There are also a variety of methods you can use to //deploy// your analytic - to use it in other ways, across a variety of tools.

===API Function===

At the most basic, every analytic can be used as an API function - a web call that can get the analytic data for your choice of date range. The data is available in a variety of formats, including...

  * JavaScript Object Notation (JSON) - used for web and IoT services
  * CSV & Tab Delimited Files - used for spreadsheets and legacy applications
  * XML - used in C#, C++ and older tools without native JSON support

===Reports===

Certain [[analytic_modules|modules]] can convert your analytic to a daily report. This has several advantages...

  * Key analytic information can be sent to people on a regular schedule (ie. daily),
  * Reports can be analysed by our machine learning system to check if they are 'normal',
  * Your [[background caching system|cache]] data is regularly generated, meaning weekly or monthly reporting will be extremely quick.

===Infographics===

Some modules can create //infographics// - interactive web-based dashboards to show live or recent information.

These deliver data to people in the field and operators, who need up-to-the-moment information.

===Alerts===

Some analytics - particularly [[module_control|Control]] and [[module_limits|Limit]] analytics - can be converted into an **alert**, to give immediate indication of issues.

Even better, you can build an analytic on a single asset and deploy it across //many//.

===Event Data Sources===

Some analytics - such as the [[module_sheartracking|Shear Tracker]] or [[module_event|Event Detector]] - can be used as a source of ARDI events.

This then allows you to easily make new analytics based on those events, or navigate through time using them.

===In Python===

In some cases, the analytic you create can be compiled into native code* for several different languages, including  Python.

This means you can build an application that uses //dynamic logic// from the ARDI server. This is extremely helpful if you'd like to make an application that works across multiple sites but may have radically different logic and infrastructure.

//* Some nodes - such as [[ardi_point|ARDI Point]] nodes or [[timing_timer|Timers]] - require specific functions to be present, or should be run in specially-created modules.