Layered Frame Analytics

Layered Frame Analytics is a method of capturing important values (such as KPIs or performance indicators) from complex data.

This type of analytic begins with a frame.

A frame represents a period or an instant in time. As well as a start and end time, can also contain any number of individual attributes which are the values of interest about that time period.

For example, a single frame might represent a day, and it might hold values for the highest and lowest temperature.

Example of a 24 Hour Frame

As well as attributes, frames can also store tables of data.

In the example below, the frame contains a table of information about the temperature throughout the day.

Example of a 24 Hour Frame

TABLE

Layers are used to create, modify and manipulate frames.

Although each individual layer will only perform a single task, they can be added together to create complex sequences.

For example, the get_query layer runs an ARDI query, getting a table of values from across the time of the frame.

The summarisevalues layer is used to summarise the values in a table and record them in the attributes of the frame.

So we can do the following…

Initial Frame

Layer: Use get_query To Read A Table Values for Temperature

New Frame with Table Values

TABLE

Layer: Get summarisevalues To Capture Min & Max

Final Result

The final result is a database record for the day containing the start and end times of the day, as well as the minimum and maximum temperature.

Working with Multiple Frames