Data Categories

Learn about data categories and how to create a new data category.

Overview

A data category represents a dataset loaded into Visier that runs on a unique data load frequency. Each data category produces its own data version and, if there are multiple data categories, each is joined to the primary data version at runtime. If there are multiple data categories, one is the primary data category and the others are supplementary data categories. A data category is a set of instructions to generate a data version. The "instructions" within a data category bring together the mappings from source data to objects in Visier's data model. For example, a mapping connects your organization's source data about your employees to Visier's Employee subject.

A data category defines how to release data versions to production, such as auto-release latest or manual release. To change a data category's release behavior, see Release Behavior.

Tenants commonly have at least two data categories: a default tenant data category for HR data and a usage data category that runs data versions about user actions in Visier.

Your tenant may have additional data categories, called supplementary data categories, to load other data alongside your primary data category, such as loading work productivity data alongside your HR data. With supplementary data categories, you can generate data versions at different frequencies, such as monthly updates for HR data and weekly updates for work productivity data. With this approach, your users will see the latest data version for each of the data categories in the solution experience.

Supplementary data categories can be useful in situations where you're adding new data, but you don't have access to the source files for the primary data category, such as if you have access to work productivity data, but not HR data. This approach lets you generate a data version that includes multiple data sources without requiring that you gain access to sensitive data.

You can designate whether a data category is primary or supplementary with the Supplementary data setting. For more information, see Create a data category.

If you're adding new data to your tenant, you must decide which data category the data mappings belong to. To make that decision, consider the following questions:

  • How often will the data be processed in Visier? If your data will be processed at the same frequency as an existing data category, use the existing data category.
  • Is there a reason to separate the data into a different data category? If you don't have a reason to separate your data, keep the data together in the same data category.

Example: Applicant data

Let's say that you already have Employee data in Visier, and now you're adding Applicant data. The Employee data is part of the Tenant data category and has a scheduled job every day. You know that you want to process your Applicant data daily in Visier, and you can't think of a reason to separate Applicant and Employee data into different categories for processing. In this scenario, you will assign your Applicant mappings to the Tenant data category.

Example: Engagement Survey data

Alternatively, let's say you already have Employee data in Visier, and now you're adding Engagement Survey data. Like the previous example, the Employee data is part of the Tenant data category and has a scheduled job every day. You don't get new survey data daily, so there's no reason to process survey data in Visier daily. If you added Engagement Survey mappings to the Tenant data category, your old survey data would be processed daily, causing your scheduled jobs to take longer. Instead, you want to process survey data quarterly to align with the frequency at which you receive new survey data. In this scenario, you can create a new data category to process survey data separately from Employee data. When a user views employee and survey data in Visier, the different data versions are both available to provide the correct data in visualizations and analyses.

To check a data category's current version, in a project, navigate to Data > Data Categories. In the list of data categories, check the Data Version column.

Create a data category

  1. In a project, on the navigation bar, click Data > Data Categories.

  2. Click Create Data Category.
  3. Type a display name and description.
  4. Click Create.

After creating a data category, configure the following:

  • Release behavior. For more information, see Release Behavior.
  • Settings. Navigate to the Settings tab.
    • Auxiliary temporal valid range: If enabled, the loader generates valid ranges (time ranges in which changes may have occurred) for auxiliary mappings based on temporal data. A valid range is a time range that a change could have occurred during.
    • Supplementary data: If enabled, allows data versions created from this data category to be loaded alongside a primary data version. If disabled, the data category is the primary data category. A tenant can only have one primary data category.
    • Output domain: Select the platform to load data into, such as Visier People.
    • Tenant setting: Select the name of the setting as specified under Data > Tenant Settings. For more information, see Tenant Settings.
    • Extraction rule: Skip none values: If an attribute is changed to a "none" value, the loader produces an error. Enable to ignore the error.
  • Optional: File sets validation. For more information, see Add File Sets to a Job.
  • Analytic object category. If an analytic object should be loaded from a different data category, you can change the Category in an analytic object's Settings. For more information, see Analytic Object Settings.

Next steps

After creating a data category and configuring its settings, do the following based on your use case:

  • If you are conducting an initial data load, the next step is to create and configure mappings to specify how the data in your source is loaded into Visier. Mappings connect the source files' columns to the properties in Visier's analytic objects. For more information, see Add a Mapping.
  • If you are uploading data files that have been previously uploaded, for example, Employee data, and you have added columns, the next step is to configure the existing Employee mapping. For more information, see Add a Mapping.
  • If you are uploading data files that have been previously uploaded without any additional columns, you have the option to 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.

    Alternatively, if your data loads are stable for this type of data, you may want to schedule your jobs to automate the data version generation process. For more information, see Schedule a Job.