In database systems, what does the Data Definition Language (DDL) accomplish—does it describe how data are structured, specify to the DBMS what is required (not how to process), and determine how data must be structured to produce the user’s view?

Introduction / Context:
Relational database management systems separate the logical description of data (schema) from its manipulation. Data Definition Language (DDL) statements create and alter schemas, tables, constraints, and views, thereby defining how data are organized and exposed to users and applications.

Given Data / Assumptions:

• DDL includes CREATE, ALTER, DROP for schemas, tables, indexes, and views.
• DDL defines structures and constraints rather than procedural access paths.
• Views (external schemas) present user-oriented structures over base tables.

Concept / Approach:

DDL describes structure by declaring tables, columns, data types, and integrity rules. It specifies what is required to the DBMS by declaring desired constraints without detailing algorithms (declarative model). It also determines structures for user views by defining views that tailor the logical representation for tasks and security needs.

Step-by-Step Solution:

Verification / Alternative check:

SQL standards classify schema and view definitions as DDL, while procedural data manipulation is handled by DML (INSERT/UPDATE/DELETE/SELECT).

Why Other Options Are Wrong:

Choosing any single item ignores the full scope of DDL.

“None” contradicts widely accepted DBMS behavior.

Common Pitfalls:

Confusing DDL with DML; remember that DDL shapes the data landscape, DML moves data within it.

Final Answer:

All of the above