Confluence Custom Charts
Overview
Confluence has become the favorite document collaboration tool for millions of knowledge workers. Any piece of corporate knowledge which requires a bit of collaboration is candidate to be on Confluence. And these teams require diverse insights from their Confluence pages. To address this need, the Confluence Custom Charts gadget presents the queried results in customizable tables and charts, allowing users to select from a range of visualization options including pivot tables, bar charts, pie charts, line charts, and more.
Whether tracking project progress, analyzing content trends, or monitoring user contributions, this gadget offers a powerful solution for visualizing Confluence page data with precision and clarity.
Search Confluence content
Queries to search for your Confluence content rely on the Confluence Query Language (CQL) to formulate searches based on criteria such as page properties, labels, creators, and modification dates, facilitating the retrieval of relevant page data.
For example, to list all the pages (type = page) in the space “Teams in Space” (space = TIS) with the label space_mission (label = space_mission) you’ll type the following CQL query
space = TIS and type=page and label = space_mission
Have a look to the complete CQL documentation to master queries in Confluence
You don’t need to rack your brains with complex CQL queries, use the set of filters we provide to retrieve your Confluence data: Title, space, creator, type, updated date. If you need more advanced searches, you can always use the CQL queries.
View type: Table
View the results of your CQL query as a table, where you can select which columns are displayed.
Group results
Group results by selected columns
If you are familiar with the GROUP BY
statement in SQL, you’ll quickly find interesting uses to group the results of your CQL. If you select to group the results by the previously selected columns, the result rows will be split into groups, based on their values. Thus, only one row will be displayed for each of the groups, so be careful because this implies constraints on the columns.
The grouping of columns is typically combined with aggregations, which moves us to the next section, where we’ll see an example.
Aggregations
Aggregations are also common in the SQL domain. These functions get the values of grouped rows as the input of that function to return a calculated value. This gadget currently supports three functions:
Count. It returns the number of rows in that group.
Min. It returns the smallest value of the range of values of the group.
Max. It returns the largest value of the range of values of the group.