Custom datasets let you take advantage of the many features unique to datasets that make them a flexible and powerful tool for data storage. To understand whether your institution's process warrants the creation of a custom dataset, lets get a taste for the attributes that make datasets unique from other objects in Slate.
Datasets' relationships to other records
Dataset records exist independently of all other records in Slate. Optionally, dataset records can have a one-to-one or one-to-many relationship with other records in Slate using Parent/Child relationships or a Related Dataset Row Field.
Methods for storing data on custom datasets
Dataset records primarily store data in custom dataset-scoped fields. These work in the same way as custom person-scoped fields.
Like person records, dataset records have a Timeline that displays messages, sources, and interactions associated with that record. The example opposite shows the timeline for an alumni volunteer custom dataset record.
Dataset records can store dataset-scoped Materials. The example opposite shows materials associated with an alumni volunteer custom dataset record.
Dataset records have built-in tables to store multiple contact devices (phone numbers/email addresses) and postal addresses, like person records.
Entities can be created for your custom dataset to store multiple rows of similar data.
Integrations with other areas of Slate
You can search for dataset records with the Lookup tool. Dataset records also have their own query base, with which you can create queries and reports that return one row per dataset record.
Custom dataset-scoped forms can be created to capture information about the dataset record, and dataset records can submit dataset-scoped forms and event registrations. Dataset records can also be autosuggested in form text fields.
Dataset records can be used to create end-user accounts, which can be used to log in to secure forms and portals. Access to dataset records can be restricted using Permissions.
Datasets cannot recreate the relationship of person records and applications. Additionally, datasets are entirely custom, and all desired features must be created by your institution.
When to use Custom Datasets, or: Does My Process Really Need a Dataset?
Creating a custom dataset is a large undertaking, and it isn't appropriate for every circumstance. Before creating a custom dataset, have a plan that addresses these questions:
- What data am I trying to collect? How will I use that data to improve my institution’s processes or data analysis?
- Is there another way to collect this data? Could a custom field and prompt list or an entity be used instead?
- Do these potential dataset records already exist in Slate as person records? Could I build on existing person records, rather than create a new dataset?
Not sure whether a custom dataset is right for your process?
Attend a community conversation to bounce your ideas off Technolutions staff, or explore the Record Management section of our Community Forums for inspiration from fellow Slate users and dataset aficionados.
Now, if you're confident a custom dataset could help your institution to organize data in a way that custom fields or an entity could not, you can get started with creating your first custom dataset.