Skip to main content
Skip to article
  • Qualtrics Platform
    Qualtrics Platform
  • Customer Journey Optimizer
    Customer Journey Optimizer
  • XM Discover
    XM Discover
  • Qualtrics Social Connect
    Qualtrics Social Connect

Load into a Data Project Task

Was this helpful?


This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

The feedback you submit here is used only to help improve this page.

That’s great! Thank you for your feedback!

Thank you for your feedback!

About the Load into a Data Project Task

The Load into a data project task allows you to take data that’s been previously imported by a data extractor task, and save that data into a Qualtrics imported data project. You can use this task to add new data records and update existing ones.

Once you’ve loaded your data into an imported data project, you can analyze your data using Stats iQ or a dashboard.

Qtip: For more information on using data loading and extracting tasks, see using Workflows tasks to build ETL workflows.

Setting Up a Load into a Data Project Task

Qtip: Before setting up your workflow, make sure you’ve already created your imported data project.
  1. Click the navigation menu in the top-left corner.
    In the workflows page, clicking "create a workflows" and then "started at a specific time"
  2. Choose Workflows.
  3. Click Create a workflow.
  4. Choose Started at a specific time.
    Qtip: You can also use the “started when an event is received” option, although we recommend using  a scheduled workflow for this task. See scheduled workflows vs. event-based workflows for more information about each option.
  5. If desired, rename your workflow.
    creating the workflow schedule, renaming the workflow, and adding a task
  6. Determine when the workflow runs. See scheduled workflows for more information.
  7. Click the plus sign ( + ) and select Task to set up your data extractor task. The extractor task imports data from one location so you can save it somewhere else. See available data extractor tasks for the options available to you.
  8. Click the plus sign ( + ) and select Task.
    clicking the plus sign and then task
  9. Select the Load into a data project task.
    choosing the load into a data project task
  10. Choose the source extract data task that contains your data.Shows how to set up a load data into project task.
    Qtip: The maximum file size for the file in the data extractor task is 1 GB.
  11. Choose a project to save the data into, or create a new project from scratch.
  12. Click Next.
  13. Now you’ll map your Source fields to your Data project fields. The source field is how the field appears in your data extractor task, while the data project field is how the field appears in your imported data project. For detailed steps, see Mapping Source Fields to Data Project Fields.
    image of mapper
  14. Click Save when you’ve finished setting up your mapping.

If you’d like to visualize your imported data project in a dashboard, see importing data as a CX dashboard source.

Mapping Source Fields to Data Project Fields

The source is the data pulled from your data extractor task. The data project is the existing or new imported data project you’re uploading the data to.

Attention: The Unique ID must have a unique value for every record in your file. This field can’t be empty.
Qtip: When data is imported, entries will be deduplicated by the specified unique ID field when setting up your imported data project. See the linked support page for more information. If your imported data project doesn’t already have a Unique ID, you won’t be able to update existing records in your project, only upload new ones.

Mapping to an Existing Project

Mapper when the project is existing. Nothing can be edited except which field is matched to another field

  1. In this setup, you match existing columns in your data source to existing columns in the imported data project.
  2. Check that the correct Unique ID field is checked for the imported data project. Match it to the Unique ID field in your source.
  3. You can see each field’s type. You can’t edit field types.
  4. Click Add Field to add more fields to your mapping.
Qtip: Sometimes field names will vary across sources, especially with metadata. For example, surveys have “Recorded Date,” which is similar to an imported data project’s “creation date.”
Qtip: Not every field will have an equivalent. For example, imported data projects have a “last updated date,” but surveys don’t have anything similar. You can delete a field if it doesn’t exist in both sources.

Option to delete a field appears when you click the 3 dots, then delete

Mapping to a New Project

Mapping to a new project lets you change field types, column names, and the unique ID

  1. Because you’re creating a new imported data project, you get to name the columns whatever you want.
  2. Select the Unique ID field.
  3. Choose the field type for each field.
  4. Click Add Field to add more fields to your mapping.

Once you complete this step for the first time, your project will be created immediately. That means that when you edit this task, you will be able to edit mappings, but you won’t be able to rename columns or choose different field types or assign a new Unique ID. To rename columns and change field types, you can find the project on the Projects page and edit it directly.

Qtip: Make sure to delete any fields you don’t want to appear in your new imported data project.

Uploading Field Mappings

For new or existing projects, you can choose to upload field mappings instead.

  1. Click Download a sample mapping.
    Data mapping window
  2. Look at the field names listed in the mapper. Use these exact names in your file. IF you’re unsure how to name a field, click the drop-down and find it in the list.
  3. Row 1 of your file should contain the names of all of your source fields.
    Spreadsheet
  4. Row 2 should contain the names of all the imported data project fields.
    Qtip: Make sure columns match the same fields together. Exclude columns of data you don’t want to include in the imported data project.
  5. Click Choose file to upload your CSV.
    Choose file button top of window
  6. You can make edits to your fields, such as changing mappings or adding more fields, before you save your changes.
    Fields listed on page change based on what's in the file
  7. Save your changes.
Qtip: You can click Remove file if you want to upload a new file.

Mapping Field Values

In addition to mapping fields to each other, you can also map individual values.

Example: You’re pulling data from a survey into an imported data project. One of these fields is a satisfaction rating question. You’d like to rename the different satisfaction ratings like this:

  • 1 should become Very dissatisfied
  • 2 should become Dissatisfied
  • 3 should become Neither satisfied nor dissatisfied
  • 4 should become Satisfied
  • 5 should become Very satisfied

 

  1. On the Map data window, click the 3 dots next to the field you want to map field values for.
    Map data window
  2. Select Map value.
  3. You can map your values by doing one of the following:
    • Upload values: You can upload a spreadsheet of all the values you want to map. Click Download CSV Template. The left column (from) should be the original value in the source, and the right column (to) should be the final value you want to appear in the imported data project. Upload this file when you’re finished.
      Choose file and download CSV template buttons at the top of a new window that opens

      Qtip: Make sure to save your changes in a UTF-8 encoded CSV.
    • Manually input values: Click Add Row to input each value. The left should be the original value in the source, and the right should be the final value you want to appear in the imported data project.
      Add row button underneath a list of recoded fields
  4. If you want to set a value for empty fields, select Map blank fields to a default value. Enter the value.
    Saving values
  5. Click Done.
  6. Save your task.

FAQs