You can enrich the Issues data cube with additional data from external data sources, like files, REST API, or SQL SELECT to a database. This way you can import new measures and new properties to Issue dimension members.
Please at first read about flex.bi bi cubes, dimensions and measures - you will need to understand the multi-dimensional data model to be able to map new source data columns to cube dimensions and measures.
From Source Data tab select Add new source application or Source Files tab to upload new source data.
On this page:
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Source data preparation
Before data import, it is necessary to see if the source data have a column a column by which which flex.bi will be able to find members you would like to map imported measures or properties. It should be either Project key, Issue key, Time dimension (see herewhich what date formats will be are recognized by by flex.bi as date or datetimedate-time), full Sprint name, or any of the member IDs or names matching the the flex.bi dimension member names.Currently, you can import additional measures only to the custom field dimensions that are created from single select type custom fields with parameter separate_table = true enabled in flex.bi advanced settings for custom fields.
If you have selected any of the source applications, please first follow the source parameter specification in flex.bi core documentation
No source parameters are necessary in the case of source file upload; you can proceed directly to preview the data that will be imported.
Column mapping
Next The next step is column mapping to Jira dimensions and defining what will be the new measures and properties. Before that
First, select Jira issue cube the Issues cube you want to import data into [1].
First, you need to specify which column Then specify to which dimensions you would like to map the imported data [2]. Select dimension and dimension hierarchy level from the available dimension list of standard-issue field dimensions and single select custom fields (for more details see Mapping to single value custom field dimensions below). In the example below, . there is a Project column that I would like to map to Project dimension Project level. In advanced options, the Name column mapped to the Project dimension, Project hierarchy level and t means data are mapped to the projects in the Project dimension.
In advanced options, specify whether the column contains Name or Key values by which flex.bi can find each dimension member [3]. In the example, the Name column is selected because the projects in this column have the name specified exactly as this project name is in in flex.bi and this is how how flex.bi will be able to find to which project each of the Measures or properties should be imported.
You can use any issue default field dimension for mapping. You can enable and use mapping to single value custom field dimensions as well.
Note that it is also possible to select advanced option Skip missing: in that case if Usually, an external data source is not identical to data in flex.bi and might contain data on projects, persons, or issues that are not imported into the particular data cube. flex.bi throws an error if the external data source has rows that do not have a match in the selected dimension and additional data import stops. To handle those use cases and complete data import for matching data, select the advanced option Skip missing [3]. If flex.bi does not find a Project member with such name as is in this column, the data from that row will is not be imported . this time and flex.bi will throw an error if Skip missing option is not selected and you have rows that do not have a match.
proceeds with the next row.
Next, it is necessary to specify how to import other columns. By clicking in any of dimensions Clicking in the Dimension field, the default import dimension will be suggested
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is suggested based on the data type.
- Number is suggested to import as Measure [4].
Note that this measure in at a detailed level will be is visible for linked dimensions only (mapped dimensions in the data mapping screen). For example, if Budget EUR is linked to Project dimension, but, in a reporta report, you will also wish to selectadd another dimension, e.g. Time dimension in Pages for filtering various time periods, only the Total Budget for All Time will be displayed, not for individual projectsOrganization, for grouping data by projects and organizations, there will be value only for All Organizations, but not for individual organizations. This is because we have not imported a Budget EUR that would depend on Project and Time, but only Project. If you wish to import number that should depends on a project only, not Project and Organization combinations (for more details see Using additional data in the report below). You may import numeric value also as property, then it could be displayed the same no matter what filter is selected, import the number as Property.To import property select the same level .
- Any column (number, string, date) could be imported as property [5]. To import a property, select the same Dimension and Level as you have selected in the column that you map by preceding column for mapping [2] and enter the Property name [5]. The property name does not have to match the Field name that is detected from the source data column header.
- Date will be is suggested to be imported as Time, if date matches supported date formats [6]. In the example below if Deadline would be , the Project end date is imported to the Time dimension then Budget would be thus the measure Budget EUR is mapped to Project and Time and could be analyzed by both dimensions.
This is not what we want in this case, so a date can also be changed to be imported as Property and Date count measureAnother option is to import date as property, measure counting rows with the date field, and map that date count measure to the Time dimension [7]. Map the date column the same way you would do for a property by selecting the same Dimension and Level as you have selected in the preceding column for mapping [2]. In advanced options, enter the Property name, a name for date count measure, and click in the field date count dimension to map the date count measure to the Time dimension. In the example below, besides "Deadline" property as well "Projects with deadline" measure will be created the project property "Planned end date", flex.bi creates new measure "Project count by end date" that combined with the Time dimension will show how many projects have a deadline a planned end date in a selected Time period.
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The rest of the columns where Dimension will is not be specified will , remain unmapped and will not be imported. You may enable the option Hide unmapped columns to see which columns are currently mapped and going to be imported.
After mapping is complete you can proceed to import. In the import status, flex.bi shows a successfully imported row count. If there will be are any errors they will be are displayed or import will stop stops on the first error. In this case, you should see the error and edit source application parameters or correct source file and upload new version for import.
Please contact flex.bi support if you need any assistance for with column mapping.
Mapping to single value custom field dimensions
flex.bi supports supports additional data import to to single value custom field dimensions with one level. Please add additional an additional separate_table parameter in the = true parameter to the custom field definition in flex.bi advanced settings:
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[jira.customfield_NNNNN]
data_type = "string"
dimension = true
separate_table = true |
Use custom field ID instead of NNNNN in the definition above. Add the updated custom field definition to flex.bi advanced settings or or ask the Jira administrator or flex.bi admin admin to do this for you. flex.bi advanced settings are common for all accounts and only Jira and and flex.bi administrators have access to them. After that run an import in the account where this custom field is selected for import as dimension. You should be able to select this custom field for additional data mapping after import.
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After successful additional data import, you can proceed to Analyze tab to include the imported data in reports.
- The Imported measures will be displayed are available in the Measures dimension as User defined measures measures.
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- Imported properties will be visible are available in the Measures dimension under the Custom properties section
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- .
If you would like to use an additionally imported measure (like Budget EUR) with other dimensions in the report, you might want to create a new calculated measure to change the measure context and tell to ignore the rest of the report dimensions. Use function DefaultContex() and list dimensions measure is related to (from mapping screen). For example, the expression for Budget EUR to look only at selected Project would look like this:
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DefaultContext((
[Measures].[Budget EUR],
[Project].CurrentHierarchyMember
)) |
Deleting additional data
While experimenting with additional data import and looking for the right data mapping, you might want to delete imported data after each iteration.
- Go to Source Data and chose the option Delete data to clear imported measures or Delete to delete the whole data source.
Go to Analyse section and open Measures. In the section, Custom properties find properties that were imported with the additional data import, open to show their content, and then select Delete.
