We’re excited to share a new Beta feature in ActionableAgile for Azure DevOps that lets you easily save your data sets! ✨
This upgrade streamlines the saving process, allowing you to access and analyze your information whenever you want. With this feature, loading your data is a breeze, so your valuable insights are always just a click away. Begin saving your data sets today and unlock a more efficient approach to analyzing your work!
Follow below for a step-by-step guide to save your data 🧙♂️
Navigate to the Data Set drop-down menu and select Create New Data Set.
Create a New Data Set
Step One: Select Work Items
This action will kick off step one of the new data loader, where you will choose what data you want to load.
Firstly, choose a unique name for your data set that is less than 50 characters in length.
- Secondly, choose whether you want to load via Board Columns or Workflow States.
For Board, select the Team and the corresponding Board you want to view.
For Work Items, select the Team(s) you want to view.
Next, pick the Nested Area Paths that you would like to use.
Lastly, choose whether you want to apply filters that limit your data to items Created After and/or Resolved After a chosen date.
Once you've settled on the parameters for the data you want to load, go ahead and click "Next."
Step Two: Add Fields
We automatically bring in these Default Fields: ID, Issue Link, Title, date, Work Item Type, Priority, Value Area, Area Path, Iteration Path, Blocked Days, Blocked, Tags, Reason, Lane, Removed From
From the list of available fields on the left-hand side, choose the field(s) you wish to bring into your data set.
Please note you can select (and deselect) multiple fields in one go.
Once you have chosen your fields, select the top arrow to add them to your data set.
Your chosen fields will now appear in the right-hand column.
To remove any fields from your data set, simply select the desired fields and click the bottom arrow to remove them.
Once you have selected your preferred fields for the data set, click “Next.”
Step Three: Map Workflow Stages
