Time series data are a series of measurements taken over time, usually at a regular interval. Some examples are measurement of sales volumes per year, total flights per day, production outputs per hour, or high frequency temperature readings at sub-second resolution.
Learn more about time series and ways to setup time series in Foundry.
In Quiver, you can directly add data modeled as time series in the Ontology from the top bar menu under Add Data > Time Series. You can also convert data with temporal nature such as object sets with a timestamp property, a chart with a temporal axis, or tabular data of values with a timestamp, into time series directly in Quiver to then use the rich set of time series analysis tools available in Quiver.
Learn more about creating time series from object sets and charts.
Quiver offers a large number of transformations and visualizations on time series.
Learn more about time series transformations and visualizations in Quiver.
In Quiver, you can conveniently visualize the time series property on a sensor object linked to a root object. Learn more about sensor object types as well as how to visualize time series properties in Quiver
Quiver also offers ways to interact with time series data through ranges; this allows you to highlight and drill down on anomalies in the data or to use time series values as input to Ontology actions.
Learn more about how to use time and value ranges.
You can create forecasts in Quiver using the Time series forecast transform.
Learn more about creating forecasts in Quiver.