Add a Mapping

Create new mappings manually or streamline your data integration using AI-augmented mapping.

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Custom profile with these capabilities: Data (Write, Detailed)

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Overview

To connect your source data to objects in Visier, you must create mappings. Mappings define the link between your source data and Visier through column association or formula calculations. This guide describes how to create mappings manually or using AI-augmented mapping.

Tip: To learn more, take the Visier University eLearning course: Mapping your data.

If you are conducting an initial data load, you must do the following before you add a mapping.

  1. Load your data into Visier. For more information, see Bring Data In.
  2. Generate sources for each data file. Sources store data for your solution, for example, Employee data is stored in the Employee source. For more information, see Create a source through file upload.
  3. Create a project in Studio to hold your work. Projects are how Visier handles version control, allowing you to define and edit the solution separately from the current production version of the solution. For more information, see Use Projects for Version Control.
  4. Optional: Create a data category for the data you are uploading. A data category represents a dataset loaded into Visier that runs on a unique data load frequency. For more information, see Data Categories.

If you are uploading data files that have been previously uploaded, for example, Employee data, and you have added columns, you need to configure the existing Employee mapping. For more information, see Configure a Mapping.

Note:  

  • You should create a mapping for every source containing data you want to load into Visier. For more information, see Sources. The number of mappings you need varies by data structure, as a single source can be used for multiple mappings. For example, a CSV file containing both employee and performance data can have two separate mappings.

  • Mapping changes made by an administrating tenant are automatically inherited by its analytic tenants.

Create a manual mapping

Use manual mapping when you want full control over column logic, formulas, and mapping settings.

Prerequisites: Your Visier tenant must contain source data and target objects, like subjects or properties, to map data to.

  1. Do one of the following:
    • In a project, on the navigation bar, click Data > Mappings.
    • In a project, on the navigation bar, click Model > Analytic Objects. Select an analytic object and then click Mappings.
    • In a project, on the navigation bar, click Data > Connectors. Select the Databricks or Snowflake connector, and then click Mappings. To set up a connector, see Sync Databricks Data and Sync Snowflake Data.
  2. Click Create Mapping > Manual mapping.

  3. Type a display name and description.

  4. Select the loaded data source that you want to create a mapping for. For more information, see Sources.
  5. Click Next.
  6. In Configure settings, select the following:
    1. In Data category, select the data category that the mapping belongs to. For more information, see Data Categories.
    2. In Mapping type, select one of the following options. For more information, see Mapping type.
      • Regular: Mappings that convert records in a source into instances in the analytic model. Conception and termination system events are created for the analytic object from the source's records.
      • Auxiliary: Mappings that augment data without the loader creating system events, such as conception or termination events.
      • Correction: Mappings that update source data or contain corrected data.
      • Lookup: Mappings that connect additional data to the data load target using any column as the key to join tables with the regular mapping. Lookup mappings require formulas or business rules to define the key column and properly augment the additional data. For more information, see Business Rules.

    3. In Target, select the Visier object to map your data to. For more information, see Understand Visier's Analytic Model.

      Note:  

      • If you created the mapping through Model > Analytic Objects, the Target is read-only and automatically set to that analytic object.

      • You do not need to select a Target for lookup mappings.

    4. In Data file type, select a data file type to determine how Visier treats your file uploads. For more information, see Data file type.

    5. In Override behavior, select the behavior of how Visier uses newer records to overwrite older records. For more information, see Override behavior.

    6. Optional: In Target group, type a target group name. This is a label that groups mappings together for updates. When there are multiple mappings in a target group, jobs compare the changes between mappings in the same target group so that data in other mappings isn't considered missing or terminated. For more information, see Target group.
    7. If Correction mapping type, select a correction type. This defines whether the correction is an insertion, edit, deletion, or restatement of existing data. For more information, see Correction.
    8. Optional: Select or de-select Run automap (without AI) to automatically connect source columns to target properties by matching similar names. This option is selected by default. If de-selected, the automap feature will not run once the mapping is created.

  7. Click Next.

    Result: The mapping is created and a summary of the newly created mapping is displayed.

  8. Optional: In the Summary dialog, select Create another mapping. This will generate a new Create mapping dialog.

  9. When finished, click Done.

    Result: The Studio Agent panel opens automatically displaying details for the mappings.

  10. In the mapping, set the following optional settings:

    1. Optional: In the upper-right corner of the mapping, enable or disable the mapping. By default, new mappings are enabled. If disabled, the mapping is not included in future data versions.
    2. Optional: In Configure > Implicit mapping, select Enabled. If enabled, Visier maps source columns to properties that have the same name (case insensitive); for example, the column job_name maps to the target property Job_Name. Additionally, implicit mapping automatically maps new source columns after Visier receives new source data. Default is Disabled for all mappings except mappings created by Direct Data Intake API. You can override implicit mappings by mapping the property in the Map tab.
    3. Optional: In Record filter, type a formula. The record filter defines logic to select or ignore records in a source. To access a preview of the records and the formula dictionary, click Enter full screen. For more information about record filter expressions, see Record filter.
  11. Now that the mapping has been created, the next step is to connect source columns to target properties. For more information, see Configure a Mapping.

Create an AI-augmented mapping

Accelerate data onboarding using AI-augmented mapping. Visier automatically analyzes source columns, maps properties, suggests new attributes to create, and pre-configures settings for your review.

The AI model used in this feature was trained on datasets that may contain historical, societal, and statistical biases and can inadvertently perpetuate these patterns in the output. Please review the outputs carefully. For more details on Visier's AI Bias prevention, see Bias Prevention and Responsible AI.

Prerequisites: Your Visier tenant must contain source data and target objects, like subjects or properties, to map data to.

Note: To automap with AI, your organization must also opt in to AI features. In the global workspace, click Settings > AI Features.

  1. Do one of the following:
    • In a project, on the navigation bar, click Data > Mappings.
    • In a project, on the navigation bar, click Model > Analytic Objects. Select an analytic object and then click Mappings.
    • In a project, on the navigation bar, click Data > Connectors. Select the Databricks or Snowflake connector, and then click Mappings. To set up a connector, see Sync Databricks Data and Sync Snowflake Data.

  2. Click Create Mapping > AI mapping.

  3. Type a display name and description.
  4. Select a source you want to create a mapping for. For more information, see Sources.
  5. Click Next.

  6. Select the specific columns you want the AI model to evaluate for suggested mapping configurations and new properties, then click Next.

  7. In Configure settings, review the pre-filled settings, including data category, mapping type, target, data file type, override behavior, and target group. For more information, see Mapping Settings.

    • Hover over the AI configured tool tip to view the reasoning behind the AI setting recommendation.  

    • Make adjustments as needed. To restore the initial AI suggestions, click Reset to AI configured settings.

      Note: Target is read-only and automatically set to that analytic object if you created the mapping through Model > Analytic Objects.

  8. Optional: Select Detect new properties. If selected, AI will analyze your source data for missing attributes. If attributes do not exist in Visier's Blueprint, AI will suggest new simple properties or leveled dimensions to create. Review and select the attributes you want to create.

  9. Click Next.

    Result: The mapping is created and a summary of the newly created mapping is displayed.

  10. Optional: In the Summary dialog, select Create another mapping. This will generate a new Create mapping dialog.

  11. Click Done.

    Result: The Studio Agent panel opens automatically, displaying details for all mappings created in the same session, including columns, properties, and recommended next steps. For more information, see Configure a Mapping.

    Tip: For lookup mappings, use Studio Agent to create the business or extraction rules.

  12. In the mapping, set the following optional settings:

    1. Optional: In the upper-right corner of the mapping, enable or disable the mapping. By default, new mappings are enabled. If disabled, the mapping is not included in future data versions.
    2. Optional: In Configure > Implicit mapping, select Enabled. If enabled, Visier maps source columns to properties that have the same name (case insensitive); for example, the column job_name maps to the target property Job_Name. Additionally, implicit mapping automatically maps new source columns after Visier receives new source data. Default is Disabled for all mappings except mappings created by Direct Data Intake API. You can override implicit mappings by mapping the property in the Map tab.
    3. Optional: In Record filter, type a formula. The record filter defines logic to select or ignore records in a source. To access a preview of the records and the formula dictionary, click Enter full screen. For more information about record filter expressions, see Record filter.

  13. Next, validate the mapping. To preview the included or excluded values in the property, click Preview. For more information, see Preview Mapping Records.

  14. When finished, run a job to generate a data version in the project. You can then preview your changes in the solution. For more information, see Run a Job.