Every relational schema can be mapped to an
equivalent associative schema
Sentences provides this capability in the form
of a a sophisticated wizard which automatically extracts SQL schemas,
detects subtype and supertype relationships amongst business objects,
and also captures the users' knowledge about their database.
Column and table names are cleansed of hyphens, underscores
etc and turned into 'proper' language.
This capability lets you see your relational data
as you've never seen it before.
The illustration below shows how data from the SQL Server AdventureWorks
sample database appears in Sentences, less than five minutes after
beginning the assimilation process.
The process has detected that the Employee table has four subsets
- Department History, Pay History, Sales Person and Address, that
Sales Person itself has two subsets: Quota History and Territory
The metacode dataform shown for Employee 3 is automatically inferred
from the schema, It shows a tab for each subset and is fully input