Custom datasets are useful for storing data as you would on a person record, but for a different type of object or constituency not included among Slate's standard datasets.

Important!

True to their name, custom datasets are entirely custom: many of the features taken for granted on the person record must be built from scratch in a custom dataset to achieve baseline functionality. These include: Display name, matching criteria, Lookup, and the "Create a New Record" form.

Before jumping into a custom dataset, familiarize yourself with the general principles of datasets. Your goal might be achievable with a Slate feature that requires a smaller commitment. 

Start a conversation in the Community Forums to find the right case for a custom dataset.

Nine steps required to create a custom dataset

To make a custom dataset, you'll do the following: 

1. Create the custom dataset

2. Create fields (including optional matching criteria fields) & prompts

3. Refresh the quartet

4. Add the query base

5. Create the Lookup

6. Create the Partial Match

7. Create the New Record form

8. Create the display name rule (if applicable)

9. (Optional) Create an index header rule

Step One: Creating the custom dataset

To create a custom dataset:

1. From the main navigation, select Database.

2. Under Records and Datasets, select Datasets.

3. Select Insert. A popup appears.

4. Configure the following settings*:

   • Status:  Inactivate datasets that are no longer used without fear of losing data associated with them.

   • Folder: Keep custom datasets organized by placing it in a folder, or create a new one by selecting Other. 

   • Name: Enter the name of the dataset.

   • Type: Connects the dataset to other Slate functionality. More than one type can be entered by separating each type with a comma. Enter one or more of the following types to link:

     • school: Autosuggests on the Schools table.

     • location: Autosuggests on the Location Name for events.

     • job: Autosuggests on the Jobs table.

     • relation: Autosuggests on the Relationships table. Adds a Relationships tab to the dataset.

   • Parent: If this custom dataset is a child dataset to a parent dataset, select the parent from the list.

   • Custom Icon (Optional): Choose a custom icon to represent the dataset records in Lookup.

5. Click Save.

*Click here for a complete listing of all setting descriptions.

With the custom dataset created, we'll move on to creating its fields and, optionally, prompts. 

Step Two: Creating custom dataset fields & prompts

Basic custom dataset fields

To create custom dataset fields:

1. From the main navigation, select Database.

2. Under Records and Datasets, select Fields.

3. Click New Field. 

3. Configure the following settings:

   • Status: Active

   • Scope Category: Records

   • Scope: Select the name of your custom dataset from the list.

   • ID: Enter a unique, computer-friendly ID. Use an easily-identified prefix at the beginning of all custom dataset field IDs for easy recognition and sorting. For example, a Volunteer dataset might have field IDs such as "volunteer_email," "volunteer_firstname," and "volunteer_lastname".

   • Name: Enter a unique, human-friendly name. This should indicate to the viewer at a glance what the field is for. Will not be displayed externally.

   • Folder: Keep custom dataset fields organized by selecting a folder, or select Other to create a new one. We recommend placing custom dataset fields in a single folder so they can be viewed simultaneously.

   • Category: Select or create a Category for your fields, if desired.

   • Field Type: Select the appropriate Field Type for your field.

4. Click Save. Repeat for each field required in your dataset.

Optional: Custom dataset matching criteria

Unlike person records, custom datasets do not come with matching criteria by default. Where person records match on first name, last name, birthdate and email, dataset matching criteria must be established using a dataset row key or a unique-for-merging field.

The key (or field) is used in Upload Dataset and upon form submission to match new records to existing records, allowing for the updating of existing records and preventing the creation of duplicate records.

Without a dataset row key or a unique field, all entries will create new records.

Custom dataset row key

The dataset row key:

• is typically controlled by the institution (using something such as a unique ID number).

• is universal for every record.

• is unique for every record.

• facilitates matching during import by referencing the related dataset.

To create a dataset row key:

1. Select Database on the top navigation bar and select Fields.

2. Click New Field. A popup appears.

3. Configure the following settings:

   • Status: Active

   • Scope Category: Records

   • Scope: Select the name of your custom dataset from the list.

   • ID: Enter a computer-friendly ID for the dataset row key. Use an easily-identified prefix at the beginning of all custom dataset field IDs for easy recognition and sorting. For example, a Volunteer dataset might have a dataset row key ID of "volunteer_dataset_row_key".

   • Folder: Keep custom dataset fields organized by selecting a folder, or select Other to create a new one. We recommend placing custom dataset fields in a single folder so they can be viewed simultaneously.

   • Dataset: Configure the field similarly to a typical person-scoped field, but select the name of the dataset within the Dataset setting.

   • Category: Select or create a Category for your fields, if desired.

   • Field Type: Dataset Row Key

4. Click Save.

Custom dataset unique for merging field

A unique-for-merging field:

• is typically related to optional data points that are most likely controlled by a third party.

  • facilitates matching during import.

To create a unique-for-merging field:

1. Select Database on the top navigation bar and select Fields.

2. Click New Field. A popup appears.

3. Configure the following settings:

   • Status: Active

   • Scope Category: Records

   • Scope: Select the name of your custom dataset from the list.

   • ID: Enter a computer-friendly ID for the dataset row key. Use an easily-identified prefix at the beginning of all custom dataset field IDs for easy recognition and sorting. For example, a Volunteer dataset might have a dataset row key ID of "volunteer_dataset_unique".

   • Folder: Keep custom dataset fields organized by selecting a folder, or select Other to create a new one. We recommend placing custom dataset fields in a single folder so they can be viewed simultaneously.

   • Category: Select or create a Category for your fields, if desired.

   • Field Type: Select the appropriate Field Type for your field.

   • Unique for Merging: Set to Value contains a unique ID which identifies a single record for merging.

4. Click Save.

Optional: Custom dataset prompts

Unlike fields, prompts don't require a scope. They can be used with any field, regardless of those fields' scope (or scopes).

To create new prompts for use with your custom dataset fields, follow the directions provided in the Prompts article. If you have a lot of prompts to enter, consider uploading in batch.

Step Three: Refreshing the quartet

Refresh the quartet: that is, the prompts cache, the fields cache, the Slate Template Libary, and the Configurable Joins library.

1. From the main navigation, select Database.

2. Under Queries, select Refresh Configurable Joins Library.

 

3. From the main navigation, select Database.

4. Under Records and Datasets, select Prompts.

5. Click the link to manually refresh the prompts cache.

6. From the main navigation, select Database.

7. Under Records and Datasets, select Fields.

8. Click the link to manually refresh the fields cache.

 

9. From the main navigation, select Database.

10. Under Configurations, select Slate Template Library.

11. Click the link to manually refresh the Slate Template Library.

With the custom dataset created, its custom dataset fields established, and the quartet refreshed, we can add the query base. 

Step Four: Adding the custom dataset query base

Query bases open up the new dataset for use in the areas of Slate that do not yet support Configurable Joins, or where Local or Slate Template Library filters are still in use.

To add the query base for the custom dataset:

1. From the main navigation, select Database.

2. Under Configurations, select Slate Template Library.

3. In the Search Library bar, enter the name of the new dataset.

4. Under Query Bases, click Add. A popup appears.

5. Set Status to Active.

6. In the Order field, enter a number. This number determines the position of the new dataset in the Lookup tool relative to other record types.

7. Select a Read Permission for the dataset query base. Leave all other settings unchanged.

8. Click Save.

Step Five: Creating the Lookup

Creating a Lookup for a custom dataset displays it in the Record Lookup tool (the order in which it will appear was set in the previous section). Lookup also determines the columns that display for the Dataset Records in the Record Lookup tool.

To create the Lookup:

1. From the main navigation, select Database. 

2. Under Configurations, select Slate Template Library.

3. Click the refresh the Slate Template Library link at the top of the page. A system dialog appears.

4. Click OK.

5. In the Search Library bar, enter the name of the new dataset.

6. Under Query Custom Exports, select one of the results from the list (it doesn't matter which) and click Add. A popup appears.

7. Configure the following settings:

   • Base: Select your new custom dataset.

   • Name: Enter Lookup

   • Default: Yes

8. Click Save. 

With the Lookup record created, we'll create the partial match.

Step Six: Creating the partial match

Partial Match creates a “search box” that can be used in the Record Lookup tool to find specific Dataset Records.

To create a partial match:

1. From the main navigation, select Database.

2. Under Queries, select Query Exports/Filters.

3. Click Insert. A popup appears.

4. Configure the following settings:

   • Base: Select your new custom dataset

   • Name: Enter Partial Match

   • Where Clause: Enter (contains(d. [index], ))

   • #1 Operators: Enter CONTAINS

5. Click Save.

With the partial match created, we'll move on to the New Record form.

Step Seven: Creating the new record form

Follow the steps laid out in the Custom Dataset New Record Form article.

Step Eight: Create a dataset display name rule

If your dataset represents people with a first and last name, or if you want to concatenate multiple field values to create the display name for a dataset record, you need to create a Dataset Display Name Rule. This ensures a display name is set for all records in your dataset, even if they are created in a manner that does not set a value for the Name (sys:name) field.

To create a custom dataset display name rule:

1. From the main navigation, select Database.

2. Under Automations, select Rules Editor.

3. Click New Rule. A popup appears.

4. Configure the following settings:

   • Name: Enter a descriptive, human-friendly name, such as Dataset Display Name Rule

   • Population: Select your new custom dataset

   • Type: Name

   • Folder: Keep custom datasets organized by placing it in a folder, or create a new one by selecting Other.

   • Non-deterministic: Rule is deterministic and has an exclusive priority

   • Priority: 1

   • Status: Preview

5. Click Save. You are redirected to the rule configuration page.

6. Set Action to Replace Values from Formula.

7. Click Export.

8. Select the fields that you will use to generate your display name.

9. Double click an export. Rename it to be computer-friendly: for example, First Name becomes first. Repeat for each export.

10. Enter a calculation formula using your exports as the variables. For records with a first and last name, a basic calculation is:
    isnull(@first + ‘ ‘, ‘’) + isnull(@last, ‘’)

11. Click Save. You are redirected to the All Rules page.

12. Select the rule from the list.

13. Click Edit.

14. Set Status to Active.

Step Nine (optional): Create index/header rules

To customize search criteria for your custom dataset, follow the the article Dataset Index/Header Rules - Customizing Dataset Record Search Criteria article.