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Analytics And Workspaces

· 3 min read
Siva Dirisala
Creator of SQL Frames

Most data analytics software that pre-aggregates data doesn't provide the ability to start from the high-level view and drill-down all the way to individual transactions. Analtyics data is mostly visualized as charts and tables. While the first-line agents that work on the transactions are able to make use of innovative visualization techniques such as kanban cards, workspaces, calendar views and other types of visualizations, analytics users are stuck to the tables and charts.

SQL Frames recognizes the advantage of the modern visualization techniques and believes that they can be adopted into the analytics workflows as well. That is why we are introducing the concept of Workspaces, a specialized data visualization technique on top of our existing tabular and chart view.

SQL Frames already supports the notion of layouts to display data in custom layouts such as card layouts so that the data can be visualized in non-tabular formats. This concept has been expanded to support the notion of first-class Workspace view type that shows the data as a list on the side with minimal data (perhaps the most important and/or record identifying data) and selecting a specific record will display the record in detail. Essentially the main focus is on the individual records and the work that needs to be accomplished within their context rather than just viewing a set of records together.

Note that both the tabular view and workspace view are important. The former provides the ability to view data of one record in the context (or relative to) of another, while the later allows focusing on the specific record to take further actions.

The easiest way to get a default workspace is to set the record identifying field(s). Optional header fields can also be specified and both these fields are used to automatically create a card layout used to render a list of records. Clicking any of them will show the corresponding record in detail.


This concept of workspace used for transactional data is adopted for aggregate tables as well. For example, the following aggregate workspace allows users to quickly view the transactional data related to the various aggregate slices.


Users can easily toggle between the workspace view and the tabular view using the Data -> Layouts menu.