Importing a Package for a Managed Data Mashup

A Managed Data Mashup is a technique for sharing data across spaces. To implement a Managed Data Mashup, a child space imports a package containing metadata from a parent space. See Managed Data Mashups.

Prior to importing a package

Before you import a package do the following:

  • Familiarize yourself with the feature's details at Managed Data Mashups.
  • Identify the joins between the parent and child spaces.
  • Create a package in the parent space. See Creating a Package.
  • Confirm that your Space Administrator user account belongs to a group that has access to the package, or that you are the creator of the package.
  • The Infor Team recommends that there be no naming conflicts between objects in the child space and the parent space. If naming conflicts are detected for dimensions and measures, Birst will merge the objects. The configuration of merged dimensions is relevant in the case of conformed dimensions where the appropriate fact selection is determined based on Birst query navigation. See Tiered Warehouses with Conformed Dimensions Example.
  • Confirm that the child space is an Advanced type space.

To import a package

  1. Go to the space where you want to import the package, the child space.
  2. Go to Admin - Customize Space - Packages.
  3. Click Import. The Import Package dialog lists the packages available for import.


    Tip: To view the contents of a package, click the View link in the Contents column. Click OK to close the dialog and go back to the packages list.

  4. Select the package to import and click Import. The contents of the package are imported into the space.

    Important: Remember that after the metadata in a package has been imported into a child space, when the metadata is changed in the parent space it is automatically updated in the child space.

  5. After importing the package, go to Admin - Define Sources - Data Flow. The imported sources from the package are identified with an asterisk (*) in front of the name and the name is italicized (for example: *Products).

To explore the contents of an imported source

  1. Right-click on an imported source to see its properties and processed data.

  2. Scroll through the data.
    Tip: Birst also shows the query that returns the data.

  3. Click Done to return to the Data Flow tab.

 

To join a child fact to a parent dimension

Best Practice: The recommended method when joining a child fact to parent dimension is to update the hierarchies and grains.

For example, to join the fact at the Product_Forecast grain to the Retail_Stores dimension:

  1. Go to Admin - Define Sources - Manage Sources - Columns. Target the child fact to the appropriate hierarchy of the parent.


  2. Go to the Grain tab and set the grains, selecting the dimensional level from the parent.

    Tip: Child facts cannot be targeted to parent dimensions that do not have the corresponding dimension tables. For example, if there is a multilevel hierarchy in the parent space, such as Categories->Sub-categories, and there is no fact in the parent that is targeted to one of the levels such as Sub-categories, then a dimension table is not created at that level. In this scenario, a user of a child space cannot select the level Sub-categories as the grain in a fact, and an error message appears: "Dimension table for this level does not exist in parent space".
  3. Click Save.
  4. Go to Process Data - Process New Data and click Process Now to re-process the child data for the updated hierarchies and grains.
  5. Create your reports and dashboards using the blended data. For example:

To join a child dimension to a parent fact

Best Practice: The recommended method when joining a child dimension to a parent fact is to use Admin - Define Sources - Data Flow.

For example, to join the child Inventory dimension to the parent Products fact:

  1. In Data Flow, right-click on a dimension of the child space and select Join to a Related Source.

  2. Drop the line on the parent fact.

  3. Specify the join.

Tips:

  • Inner, Left Outer, Right Outer, and Full Outer join types are supported.
  • For joins based on multiple keys, press Cntrl and select the keys for both the source and the target.

  1. Repeat for additional joins if needed.
  2. Create your reports and dashboards using the blended data. For example:


Next Steps