This page discusses several core concepts that are fundamental to understanding the Quiver application:
Exploration and analysis in Quiver are performed through the use of cards, which can be chained together to perform complex operations. Some cards create charts or perform calculations, while others are used to manipulate your data by filtering, joining, deriving new columns, and so on.
Every card in Quiver takes zero or more inputs, and produces an output of a specific type, for example object set, time series, categorical chart, number, etc. Together, these types form Quiver’s data model, and define how cards can be chained together.
An analysis in Quiver consists of one or more canvases, which act as an organizational container for cards. Newly-created cards are added to a canvas, where they can be viewed, configured, resized, and rearranged. Unlike a Contour path, a Quiver canvas is used for display and organization only. Rearranging cards in your canvas will not affect the underlying sequence of data transformation. Similarly, removing a card from your canvas will only delete the card if the card is not referenced by any other cards.
To understand the dependencies between cards in your analysis, Quiver also provides a graph view. In the graph, cards are represented by nodes and have edges to their input and output cards.
Learn more about the canvas and graph.
In Quiver, objects from the Ontology are used as the primary data input for tabular analysis. Quiver natively supports many different cards for filtering, transforming, and visualizing objects data.
For advanced transformations on objects data, such as deriving properties and joining between linked objects, users can also leverage Quiver’s suite of transform table, materialization, and function cards.
Learn more about object analysis.
Quiver has first-class support for time series analysis. Time series are primarily added to Quiver through time series properties, however time series syncs can also be viewed directly.
Quiver provides an extensive library of transformations and visualizations for time series data. Quiver also supports advanced time series workflows such as anomaly detection and event analysis.
Additionally, time series transformations can be saved as derived series, or used to create alerts with time series automations.
Learn more about time series analysis.
With Quiver, you can build interactive dashboards that display the results and findings of your analyses. These dashboards can be used as standalone views, or embedded in other Foundry applications such as Workshop.
Quiver parameters allow you to easily switch between different views of the data and results. After creating parameters, you can use them in your cards and expose them in your dashboard. This allows end users of a dashboard to interact live with the data and results presented.
Quiver analyses are saved manually by clicking the Save button in the top right of the application. A version history is also provided, allowing you to view or revert your analysis to previous saved versions. Additionally, in between each Save action, Quiver auto-saves your "working" state (storing it in the state URL variable, for example state=j05na7mun3). This allows you to refresh your page and get back your exact analysis state even if you have not saved. Note that if you are sharing a URL link with the state variable set, this will open that working state rather than the latest analysis version.
If multiple users are working on the same analysis at the same time, they are able to work independently without interference, however saving changes will overwrite each others saved changes.