Document Workflow Custom Charts

The Document Workflow Custom Charts gadget lets you create customized charts and tables using data from Comala Document Management (CDM) and Confluence fields.

It offers the ability to visualize and analyze document lifecycles, workflow statuses, and other crucial metrics by leveraging workflow parameters as well as essential fields like Workflow name, Last state transition date, Pending Approvers, Finished Approvers, Due date, and more. This feature-rich tool is designed to facilitate informed decision-making and improve document management efficiency. Thereby, enhancing the overall visibility of your documentation and aiding in the improvement of compliance control across Confluence spaces.

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Queries 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 can use the following CQL query:

space = TIS and type=page and label = space_mission

The Comala Document Management app provides several CQL fields that can be used to filter your search. Find all workflow CQL searchable fields listed in Comala Document Management CQL Rest API page together with the Atlassian Confluence CQL fields. We’ll see some examples in the next section.

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Confluence fields, CDM built-in fields and workflow parameters together in a table view

See the following topics to learn about our macros

Available Confluence fields: Title, Space, Type, Last Modifier, Last Modified Date, Labels, Creator, Created Date.

Available CDM built-in fields: Workflow Name, Current State, State Start Date, State Started by, Final State, State Due date, Final Version Date, Pending Approvers, Finished Approvers, Last Final Version Approvers, Current Pending Approvals, Current Approved Approvals, Current Rejected Approvals.

Workflow parameters are customizable placeholders for values such as reviewer names, content expiry durations, labels, categories, departments... Users can update these reference values as needed, to ensure flexibility throughout the workflow process.

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Example of a workflow parameter called “Department”

Available workflow parameters: Those configured by users, more information https://appfire.atlassian.net/wiki/spaces/CDML/pages/649726186.

Write the following in the CQL input field:

1.- Pages with a workflow and pending to approve by user Mike

awphasworkflow = "true" AND approvalassignee = "Mike"

2.- Pages with a workflow already approved by user Mike

awphasworkflow = "true" AND approver = "Mike"

3.- Pages with a workflow in the Rejected state

awphasworkflow = "true" AND state = "Rejected"

4.- Pages that transitioned to the Approved state during the last month

state = "Approved" AND statechange >now("-1M")

5.- Pages with a workflow named "Editor and staff approval workflow" that transitioned to the Ready state during the last month AND pending to approve by user cowens

awphasworkflow = "true" AND approvalassignee = "cowens" AND state = "Ready" AND workflowName = "Editor and staff approval workflow" AND statechange >now("-1M")

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Example #5

See more CDM built-in fields to improve your CQL filter:

• https://appfire.atlassian.net/wiki/spaces/CDML/pages/649693514

• https://appfire.atlassian.net/wiki/spaces/CDML/pages/649824034

View the results of your CQL query as a table, where you can select which columns are displayed.

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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 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.

example For example, if we want to calculate how many pages with a worfklow are in each space with a state “Approved”, use the following CQL awphasworkflow = "true" AND state = "Approved" , add space as a column, enable group result and add an aggregation to count the number of pages.

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The 1D Pivot Table view shows a perspective on your data in a single dimension (1D) of your dataset. In other words, one level of grouping, expressed when you select the value for the Rows field.

Users can select a specific attribute or field to act as the basis for organizing and aggregating data. The resulting table presents a clear representation of the chosen dimension, summarizing key metrics and allowing for efficient analysis.

The elements of the 1D pivot table are as follows:

• Rows (dimensions) The selected row represents the Confluence field used for grouping.

• Aggregation Aggregations get the values of grouped rows as the input of that function to return a calculated value. Check the aggregations section.

• Field The displayed field values depend on the chosen aggregation type.

The 2D Pivot Table view introduces a second dimension (2D) to expand on the capabilities of the 1D Pivot Table. Select 2 different fields (rows and columns) to cross-tabulate data to analyze data across both dimensions simultaneously.

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The elements of the 2D pivot table are as follows:

• Rows (dimensions) The selected row represents the Confluence or CDM field that is used for grouping.

• Columns (dimensions) The selected column represents the Confluence or CDM field that is used for grouping.

• Aggregation Aggregations get the values of grouped rows as the input of that function to return a calculated value. Check the aggregations section.

• Field The displayed field values depend on the chosen aggregation type.