Dataverse Essentials
Dataverse is the structured data layer under the Power Platform. Before Lab 2 has you build a table, it helps to know what tables, columns, and relationships actually mean here.
Why not just use a SharePoint list?
You'll actually use both in this course. SharePoint lists are quick and familiar, and Lab 3 uses one for exactly that reason. Dataverse is the step up: it enforces column data types and relationships more strictly, supports row-level security, and — most relevant to Lab 7 — every column has a stable logical name you can filter on in a trigger, independent of what you rename the display label to.
Tables, columns, rows
- Table — a structured collection of records, equivalent to a database table. Lab 2 creates a custom
Opportunitytable. - Column — a field on that table with a defined data type: text, number, date, currency, choice, or lookup.
- Primary column — every table's required "name" column, shown wherever the record needs a human-readable label.
- Row — one record. In Lab 2's Opportunity table, each row is one sales opportunity.
Column types you'll use
Relationships
A lookup column is how one table points at another. In Lab 2, adding an Account lookup column to Opportunity lets each opportunity reference an existing account record — the same pattern behind customer/order, or task/project relationships in any relational system.
Logical names — why Lab 7 needs them
Every column gets two names: a display name (what you see in the UI, and can rename anytime) and a logical name (an internal, prefixed identifier set once and never changed automatically). Dataverse triggers in Power Automate — the kind Lab 7 builds — filter on logical names, not display names, so that renaming a column later doesn't silently break your flows.