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Modifiers

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Modifiers define the business scope for statistical data. Use them to qualify data across multiple dimensions for analyzing specific business scenarios, such as "Shanghai region" or "fresh food stores". A modifier can be combined with an atomic metric and a period to form a derived metric.

Overview

A modifier is a business qualifier that defines or narrows the scope of statistical data. For example, when calculating the sales amount for online channels and fresh food stores, "online channel" and "fresh food store" are the modifiers that define the business scope. One or more modifiers, an atomic metric, and a period together form a derived metric, which reflects the status of a specific business activity. For more information, see Derived metrics.

Create a modifier

  1. Go to the Modifier page.

    1. Log on to the DataWorks console. In the target region, click Data Development and O&M > Data Modeling in the left-side navigation pane. Select a workspace from the drop-down list and click Go to Data Modeling.

    2. On the Data Modeling page, click Data Metrics in the top navigation bar. Then, in the left-side navigation pane, click Modifier to go to the Modifier page.

  2. On the Modifier page, click the 新建 icon to create a Modifier.

  3. Configure the modifier parameters.

    Parameter

    Description

    Modifier Type

    • Common Business Modifier: A general, flexible modifier. Its value is typically a user-defined business tag or text and is not directly tied to a specific dimension table.

    • Dimension Enumeration Modifier: A structured, controlled modifier. Its value must be a member (an enumerated value) from a predefined dimension table.

    Abbreviation

    The English abbreviation of the modifier.

    It serves as a unique identifier for the modifier and cannot be changed after creation. For example, fresh_store.

    Name

    The English name of the modifier. For example, Fresh Food Store Type.

    Display Name

    The display name of the modifier. For example, Fresh Food Store.

    Effective Scope

    Defines the business scope for data collection. For example, stores that sell fresh food items.

    Owner

    The user responsible for the modifier. By default, this is the user who created it.

    Description

    A brief description of the modifier.

    Data Layer

    Click Advanced Settings, and then select the data warehouse layer for the modifier: application layer or DWS.

    Mart/Subject

    When Data Layer is set to application layer, select the Data Mart or Subject Area for the modifier.

    Business Category

    When Data Layer is set to summary data layer, use this parameter to associate the modifier with a data domain.

    Data Domain

    When Data Layer is set to DWS, select the Data Domain for the modifier. You must create a data domain before you can configure this parameter.

    Associated Dimension Table

    When Modifier Type is set to Dimension Enumeration Modifier, configure the dimension to associate with the modifier.

    Dimension Table: From the drop-down list, select a submitted dimension table. For more information, see Create a logical model: Dimension table.

    Field in Dimension Table: After you select a dimension table, select a dimension attribute from the table as the associated dimension.

    Lookup Table to Associate

    When Modifier type is set to Dimension enumeration modifier, you must configure the lookup table to associate with the modifier.

    Lookup Table: From the drop-down list, select a created lookup table. For more information, see Data Standards: Lookup Tables.

    Enumeration Value: After you select a lookup table, you can select an encoded value from it to use as the enumerated value.

  4. Click Save to create the modifier.

Import modifiers in bulk

To create multiple modifiers at once, use the bulk import feature. DataWorks provides a template that you can fill out and upload.

  1. On the Modifier page, hover over the 导入 icon and click Import from Excel.

  2. On the Confirm Import Type tab, select Modifier for Import Type, download the corresponding template, and fill it out based on your business requirements.

    Note

    After selecting an import type, preview the template to prepare your content.

    The modifier import template includes the following fields: Data warehouse layer, Business category (summary data layer), Data domain (summary data layer), Data mart/subject area (application layer), Modifier type, Abbreviation, Display Name, and Name. After you fill out the template, click Next.

  3. On the Data Import tab, upload and preview your data file.

    You can choose to preview data for objects with names that already exist in DataWorks. You can then delete or modify these fields as needed.

    • Import Mode: If an imported object shares a name with an existing object in DataWorks, you can either skip the import of that object or overwrite the existing object with the imported data.

    • Import Status:

      • Import and Save: Imports and saves the data without creating a new version.

      • Import and Submit: Imports the data and submits it as a new version.

    • Bulk import limits:

      • File format: Only the .xlsx format is supported.

      • Data volume: You can import a maximum of 30,000 entries at a time.

      • File size: Cannot exceed 10 MB.

  4. View the import results.

    On the Complete tab, you can view the details of the import result. In the details list, click View More Details next to a modifier to open its edit page. If an import fails, use the error details to resolve the issue and re-upload the file.

Next steps

A modifier combines with an atomic metric and a period to create a derived metric. If a modifier is used in any derived metrics, you must delete those metrics before you can delete the modifier. For more information, see Derived metrics.

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