In data warehousing, a star schema consists of:
* A central fact table (containing measures such as sales, quantities, amounts)
* Multiple surrounding dimension tables (such as date, product, customer, location) A core characteristic of a star schema is that the dimension tables are denormalized:
* Each dimension table is usually wide and contains descriptive attributes in a single table (rather than being broken into multiple normalized tables).
* This design simplifies queries and improves performance for analytical workloads.
Why the other options are incorrect:
* A. It has a tabular structure.All relational schemas (OLTP and OLAP) are tabular; this is not unique to star schemas.
* B. It stores transactional data.Transactional data is typically stored in normalized OLTP relational databases, not in star schemas (which are optimized for analytics).
* C. It stores unstructured data.Star schema is a structured relational design, not used for unstructured data (e.g., text blobs, images).
Therefore, the defining characteristic listed in the options is: It has denormalized dimension tables (D).
CompTIA Data+ Reference (concept alignment):
* DA0-001 Exam Objectives - Data concepts and environments: schema design (star vs snowflake).
* Common data warehousing references describe star schema as: fact table + denormalized dimension tables optimized for analytics.