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FYI, the above video is for our legacy loader only. A new video will be coming for the new data loader.

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excludeWhat changes?

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Load a Board by Team has now changed name and is now “Load Team Board (by Column). Why this change? We are testing a new way to load your data, this new name helps accurately differentiate between the two ways to load data.

Load Team Board (By Column)

To Load your Azure DevOps Data

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Our new Data Loader is out! The new data loader offers two ways to load your data:

  • Board History will show only the data related to the chosen board.

  • Work Item History will show all data related to the work item regardless of which board(s) it was on and when.

How to Load Data in Azure DevOps

To load your Azure data, click on the folder icon and choose the dropdown option labeled “Load Azure data.”

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Load Team Board (by Column)

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The first thing you’ll do is choose the team and decide whether or not

is now our legacy loader. You can find it under the folder drop-down menu.

You can pull data from two options: Board History and Work Item History.

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Loading by Board History

Create a data set:

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Step 1: Select your team

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Step 2: Choose which Board you want to load.

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Step 3: Choose whether to include items in nested area paths

. You can also

or not.

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Remember to choose to either include all area paths or

only use

the default area paths

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Next you’ll choose which board you want to load.

You can also decide to only load items created after a certain date. If you choose to do so, check the box and then click the calendar icon to select the desired date. Once you’re done, click Continue.

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At this point, ActionableAgile should load your data and present you with the Cycle Time Scatterplot chart.

Load Team Data (By State)

What changes?

We are giving users more flexibility on how to load their data. There’s a new option called “Load Team Data (by State).” This is because you’ll be asked to help map Azure states to ActionableAgile workflow stages.

Why use this new feature?

if you wish to load the nested items.

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Step 4: Filter by creation date (optional)

Once you have selected the box to only load issues created after, click on the calendar to choose the date.

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Once you are satisfied with your selection you can press

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. This will take you to the Choose Additional Fieldswindow.

Loading by Work Item History:

  • You can now see data from your issues' entire history and not just that of what is on the current board.

  • You are no longer forced to lose historical data when you make changes to your board design.

  • You can measure flow for multiple teams at once allowing a higher-level view of flow.

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Loading by Work Item History was our Load Team Data (by State)

is our new Beta feature

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Please note that “Load a Board by Team” has now been renamed “Load Team Board (by Column)”

How to load by State

titleBETA

Create a data set:

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Step 1: Select your team or teams

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You can now look at data from multiple teams at once!

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Step 2: Choose whether to include items in nested area paths or not.

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Remember to choose to either include all area paths or the default area paths if you wish to load the nested items.

Step 3: Filter by creation date (optional)

Once you have selected the box to only load issues created after, click on the calendar to choose the date.

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Once you are satisfied with your selection you can press

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Choose additional fields

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Choose Additional Fields:

Here is the list of fields we pull automatically

You can also add fields that might be relevant to your analysis.

Once you have selected all the needed fields, press

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You will then see the list of all the default fields and the one you just added

Once you are satisfied with your selection you can press

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Check

your workflow mapping

Workflow Mapping:

Our workflow mapper creates a workflow stage (aka column) for each status (item in the column). You should order the columns to model the lifecycle of work. If you see the image below, Releasing should come before Resolved so you would drag the column and drop it between Active and Resolved. This is very much like configuring your board, except that you cannot reuse statuses in multiple workflow stages.

Accurately modeling your workflow is the most critical part of measuring flow as it defines the workflow that we’re measuring work through. You want the stages of the lifecycle to be in linear order from left to right. Need to manage cyclical work or want other tips? Read our blog post.

Why is this step important?

We are now pulling the historical states from all the work items and not just their current states. This gives us more accurate data and less data loss. A work item can now have moved through different boards, we will be able to follow how it moved through your workflow. Until now, we would have lost everything that happened outside of the current board the item is in. Same if you changed your board and deleted a column, all the time spent in this column would have been deleted. But not anymore!

How does it work?

Each column represents an ActionableAgile workflow stage.

Each column contains one or more workflow states.

Even though Azure doesn’t allow you to map more than one state to your board columns, you can override that here. For instance, in your closed column you can have every state that represents closed such as Closed, Done, Cancelled, and/or Abandoned

Unmapped states are states found in your work items' history that are not currently mapped to your board.

Tip

We recommend to always map these states as they carry data and will give you more accurate information on your flow. You can create new columns if needed!

You can change the configuration of the board by:

  • Deleting a column:

Note

Remember to relocate the workflow state to a different column before deleting the column

  • Creating a new column

  • Merging columns

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To move workflow stages or workflow states around, you can simply drag and drop them!

Once you are satisfied with the mapping, you can press

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titleFINISH

At this point, ActionableAgile should load your data and present you with the Cycle Time Scatterplot chart.

Your data are now loaded! 🥳


If you have any questions about this process, please submit them to our help desk.