MIS 370 Midterm (CH 1-6)

Flashcards for database systems course reviewing key vocabulary terms and definitions.

Data

Raw facts, such as 482025 Econ101.

Information

Processed, organized data that helps make smart decisions.

Database

A structured collection of related data.

DBMS

Software that manages the database.

Single-user Database

Supports one user at a time (e.g., MS Access).

Multi-user Database

Supports multiple users (e.g., Oracle, MySQL).

Centralized Database

Data stored in one location.

Distributed Database

Data stored across multiple locations.

Cloud Database

Database hosted online (e.g., AWS, Azure).

Operational Database

Supports daily tasks and transactions.

Analytical Database

Used for reporting trends and business intelligence.

NOSQL Database

Flexible format used in big data apps (Unstructured).

Data Redundancy

Same info in multiple places.

Structural Dependence

Apps break if file structure changes

Data Dependence

Data access tied to file structure.

Data Redundancy

Duplicated data everywhere.

Data anomalies

Errors when updating inconsistent files.

Metadata

Data about data.

Data Modeling

Creates a conceptual blueprint of data structures for a specific problem domain.

Data Model

A simple, often graphical representation of complex real-world data structures.

Entities

Things or objects.

Attributes

Properties of entities.

Relationships

Associations among entities.

Constraints

Rules to ensure data integrity.

Entity

A person, place, or thing (e.g., Student, invoice).

Attribute

A characteristic of an entity (e.g., StudentID, Name).

Relationship

Association between entities (e.g., student enrolls in courses).

Constraint

A restriction on data (e.g., StudentID must be unique).

Business Rules

Describes policies, procedures, or constraints on data operations.

Hierarchical Model

Upside-down tree structure with 1:M relationships only; complex and inflexible.

Network Model

Supports M:N relationships using record types and sets; still complex and hard to manage.

Relational Model

Uses tables/relations; data independence and conceptual simplicity; dominant due to SQL and ease of use.

Entity Relationship (ER) Model

Graphical representation of entities and relationships; used as a design tool, not an implementation model.

Object-Oriented Model

Combines data and behavior in objects; supports inheritance, encapsulation, and polymorphism.

Object-Relational and XML

Mix of relational model with object-oriented features; XML support for web and unstructured data.

NoSQL and Big Data Models

Schema-less, highly scalable; designed for Big Data; includes key-value, document, columnar, and graph databases.

External Model

User's view of the data.

Conceptual Model

Global view of the entire database; independent of hardware/software.

Internal Model

How data is stored logically; DBMS specific.

Physical Model

How data is stored physically on hardware

Relational Model

Developed by E.F. Codd in 1970; lets users focus on how data is logically organized, not how it's stored physically.

Table/Relation

A two-dimensional structure.

Rows/Tuples

Represent individual records.

Columns/Attributes

Represent characteristics of the record.

Functional Dependency

If attribute B is functionally dependent on A, then A -> B.

Partial Dependency

Non-key attribute depends on part of a composite key.

Transitive Dependency

Non-key attribute depends on another non-key attribute.

Primary Key (PK)

Uniquely identifies each row.

Candidate Key

Could be a primary key.

Superkey

Any combination of attributes that uniquely identifies a row.

Foreign Key (FK)

A primary key from another table; used to establish a relationship.

Composite Key

Made up of two or more attributes.

Entity Integrity

No part of a primary key can be NULL.

Referential Integrity

Foreign key values must match primary key values in the related table or be NULL.

SELECT

Chooses rows; filters data.

PROJECT

Chooses columns.

JOIN

Combines related tables.

UNION

Merges rows from two tables.

INTERSECT

Rows common to both tables.

DIFFERENCE

Rows in one table but not the other.

PRODUCT

Combines all rows of two tables.

DIVIDE

Finds rows in one table that match all values in another.

Data Dictionary

Stores metadata (data about data).

Entity Relationship Diagrams (ERDs)

Visually describe real-world data with database design.

Entities

Things we store info about.

Attributes

Characteristics of entities.

Relationships

How entities are linked

Entity

A person, place, thing, or concept.

Attributes

Describe the properties of an entity.

Simple attributes

Cannot be divided (e.g., Age).

Composite attributes

Can be broken down (e.g., Name: First, Last).

Single-valued attributes

Holds one value.

Multivalued attributes

Holds multiple values; requires special treatment.

Derived attributes

Can be calculated (e.g., Age from Date of Birth).

Relationship

How entities are associated.

Connectivity

Type of relationship.

Cardinality

Number of entity instances involved (min, max).

Existence-dependent

An entity cannot exist without another.

Weak Relationship

PK of the parent appears in the child as a non-identifying FK.

Weak Entities

Cannot exist without being linked to a strong parent entity.

Optional Participation

Is not required.

Mandatory Participation

Is required.

Unary/Recursive

Entity relates to itself (e.g., EMPLOYEE supervises EMPLOYEE).

Binary

Two entities involved (most common).

Ternary

Three entities involved (less common)

Associative/Composite Entities

Used to resolve M:N relationships into 1:M; acts as a bridge table.

Extended Entity Relationship (EER)

Adds nuance to traditional ER systems and Helps models more complex relationships and large diagrams with supertypes, subtypes and inheritance.

Supertype

A generic entity (e.g., EMPLOYEE).

Subtype

A specific version of the supertype (e.g., ENGINEER, ACCOUNTANT).

Specialization Hierarchy

Shows how subtypes break off from the supertype

Inheritance

Subtypes inherit all attributes and relationships of the supertype.

Subtype Discriminator

An attribute in the supertype that determines the subtype.

Disjoint Constraint

An instance can belong to only one subtype.

Overlapping Constraint

An instance can belong to multiple subtypes.

Total Completeness

Every supertype instance must be a member of a subtype.

Partial Completeness

A supertype instance may or may not belong to a subtype.

Entity Clustering

Groups multiple related entities into a cluster entity; used to simplify complex ER diagrams and improve readability.

Natural Key

Derived from real-world data (e.g., SSN).

Surrogate Key

Artificial, system-generated (e.g., auto-increment ID).

Fan Traps

Occur when a model has multiple 1:M paths that lead to incorrect assumptions.