A retail analyst is learning how Microsoft Dataverse organises the data their loyalty app uses. In Dataverse, what is the structure that holds a set of rows and columns, where each column is designed to store a certain type of data?
- AA table, which is a set of rows and columns that models business data Correct
- BA business rule, which validates entered data across the columns it covers
- CA solution, which packages the components that makers build and ship
- DA dataflow, which transforms source data on its way into the store
Why A is correct: Correct. The grounding defines a table as a set of rows (records) and columns (fields), with each column designed to store a certain type of data such as name, age or salary; tables are how Dataverse organises stored business data.
Why B is wrong: A business rule is real Dataverse logic for validation, but the grounding describes it as server-side logic applied to a table, not the structure that stores the rows and columns themselves.
Why C is wrong: Solutions are a genuine Power Platform construct referenced in the grounding for importing definitions, but they package components for deployment rather than store the rows and columns of business data.
Why D is wrong: Power Query dataflows do bring data into Dataverse per the grounding, but they are an import mechanism and not the structure that holds the stored rows and columns.