Lesson 11

This module showed how business objects become entities and how their characteristics become attributes for an ER model. You learned why every attribute needs a well-defined domain, how to identify and resolve multi-valued attributes to satisfy First Normal Form (1NF), and how constraints (keys, checks, and foreign keys) protect data integrity across the schema.

1. Define entities and their attributes.
2. Explain the purpose of entity identifiers (primary keys).
3. Apply two rules for creating robust identifiers.
4. Describe instances of entities (rows) and how they are identified.
5. Describe attribute domains and common domain types.
6. Recognize the problem with multi-valued attributes (1NF violation).
7. Resolve multi-valued attributes by adding targeted attributes (small, fixed sets).
8. Resolve multi-valued attributes by creating a new entity (open-ended sets).
9. List and use entity/attribute constraints to enforce integrity.

The single-value rule states that each attribute holds one value per row. Storing lists in a single column breaks 1NF and causes ambiguity, slow searches, and update anomalies.

Incorrect (violates 1NF)

CustomerID	CustomerName	PhoneNumbers
1001	John Doe	555-1234, 555-5678
1002	Jane Smith	555-9999

Correct (follows 1NF)

Customers

CustomerID	CustomerName
1001	John Doe
1002	Jane Smith

CustomerPhones

PhoneID	CustomerID	PhoneNumber
1	1001	555-1234
2	1001	555-5678
3	1002	555-9999

• Prevents anomalies: clean inserts/updates/deletes.
• Improves performance: values are indexable and filterable.
• Clarifies meaning: each value has its own row and constraints.

1. attribute: A property of an entity; implemented as a column.
2. base table: A table stored on disk (as opposed to a view).
3. BLOB domain type: “Binary large object” used for binary data (e.g., images).
4. Boolean expression: A comparison/conditional expression that evaluates to TRUE or FALSE.
5. conceptual model: Technology-neutral description of entities, attributes, and relationships.
6. data value: The value stored at the intersection of a row and column.
7. data integrity: The accuracy, consistency, and validity of stored data.
8. domain: The allowed set of values and rules for an attribute (type, range, format, nullability).
9. domain constraints: Rules enforcing an attribute’s domain (e.g., CHECK, FK to a code table).
10. entity: A business object stored in the database; typically implemented as a table.
11. instance of an entity: One occurrence of an entity; a table row.
12. key attribute: An attribute (or minimal set) that uniquely identifies an entity instance.
13. multi-valued attribute: An attribute attempting to hold more than one value; violates 1NF.
14. non-key attribute: An attribute that describes, but does not identify, an entity.
15. requirements analysis: The stage where data needs and constraints are gathered.
16. single-valued attribute: An attribute that holds exactly one value per entity instance (1NF compliant).

The next module introduces entity relationships and how to model them correctly in an ER diagram.

Before moving on to the next module, click the Quiz link below to check your understanding of entities and attributes.
Entities and Attributes - Quiz