A data type identifies what a value represents and constrains how automation or a database stores and uses it. In PowerShell-driven workflows, type information turns loosely structured test data into values that can be applied reliably. section 6.2.3 section 7.1.1
Choose types according to the destination and the meaning of each value:
- For registry checks, add a Type property such as DWORD, then add Data containing the value to set when a check fails. Defaulting Data from the first test value accelerates structure generation, while exceptional entries can be corrected afterward. section 6.2.3
- For SQL columns, map values to types such as int, float, double, real, decimal, nvarchar, uniqueidentifier, or bit according to their size and meaning. section 7.1.1
- Treat strings deliberately: nvarchar supports Unicode and requires a maximum length; nvarchar max can hold approximately one billion characters but is usually inefficient. section 7.1.1
- Decide nullability separately from the type. Require values that identify or reference source records, but allow null when a field may legitimately be absent, such as a server cost center. section 7.1.1
Generating typed registry-resolution data
Import the existing JSON, project every object with two added properties, and export the result as a new file: Type defaults to DWORD, while Data takes the first test value. This creates a reusable starting point instead of manually editing every entry. section 6.2.3
