Store Appeal Data in a Dataset for Advancement
  • 09 Nov 2023
  • 2 minute read
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Store Appeal Data in a Dataset for Advancement

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Article Summary

Advancement offices have historically created prompt lists to store appeals data. However, if your process involves tracking a lot of data within each appeal, storing all that data in a prompt list can be cumbersome. To allow for the setting of additional data points and to improve reporting, you can now use an appeal dataset to store the appeal data.

When creating gifts on a record, use the autosuggest box to find the appeal you want to use.

Autosuggest_Appeals.png

Starting from Scratch

If your institution has yet to set up appeals data in your database, setup is as simple as setting up a fund (another type of dataset record):

  1. From the navigation, select Database. 

  2. In the Records section, select Datasets.

  3. Click Insert. A popup appears.

    • Name: Give your appeal a name.

    • Type: gift_appeal

Insert_New_Dataset_Record.png

  1. Click Save.

  2. Either manually or via import, add records to the dataset.

Migrating Existing Appeals Prompts to an Appeals Dataset

For institutions already using appeals prompts, the appeals dataset is all or nothing: if a dataset with the "gift_appeal" type exists, existing appeal prompts will not be used. Since your institution may already have gifts that use the appeals prompt list, we've created a briefcaseable query that walks you through the migration process.

Migration Process

Briefcase ID:

a358facd-4f34-0b66-ea06-96b5c906238f@slate

In this process, you will:

  1. Create a dataset with the type staging_appeal.

  2. Run the query. It will re-create all existing gift_appeal prompts as records in the new dataset. (If the prompt already exists based on the ID, it will be skipped, so there's no need to worry if you accidentally run it more than once).

  3. The name of the record will be set to the value of the prompt, and the active status of the record will be set to the active status of the prompt.

  4. Once they've been created, you can perform any additional adjustments to the records (either manually or via import).

  5. When you're ready to transition to using the dataset instead of prompts, update the appeal dataset type to gift_appeal (replacing "staging_appeal").

You will also find these steps in the briefcase query description in Slate.

Important!

It is recommended that you follow these steps in your test environment to confirm the effects on your individual database before attempting in a production environment.

If you make the switch as described above and decide you aren't quite ready yet, you can undo the process:

  1. In the new appeal dataset, set the type back to staging_appeal.

  2. You can now use your appeal prompts. The briefcase process does not remove these prompts.

Housekeeping

Once you've migrated your appeals prompts to the new appeals dataset, there are a few things to do to enjoy its benefits fully:

  1. Create a local query base for the appeals dataset. This allows you to create exports and filters.

  2. Create the local exports and filters for Lookup and Partial Match, so the dataset appears in search results like other records.

  3. Refresh the Configurable Joins library (Database → Refresh Configurable Joins Library) so that joins for the appeals dataset appear. This will also happen automatically overnight.

Mapping to Appeals

In imports and forms, you may continue to use value mappings as before, but you'll also find an added destinations of Appeal - Key to which you may send the key of the dataset record.

Destination_-_Appeal_Key.png


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