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PRELIM REVIEWER > CC105 > Flashcards

CC105 Flashcards

1
Q

Raw facts that can be processed to extract meaning.

A

Data

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2
Q

A structured collection of data.

A

Database

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3
Q

Data that has been processed and organized to provide meaning.

A

Information

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4
Q

Data that describes other data, providing context and meaning.

A

Metadata

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5
Q

Software that manages databases.

A

Database Management System (DBMS)

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6
Q

Individuals responsible for managing and maintaining data integrity.

A

Data Administrators

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7
Q

People who interact with the database to retrieve or manipulate data.

A

End Users

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8
Q

Advantages of Database Approach

A

Program-Data Independence
Minimal Data Redundancy
Improved Data Sharing
Enhanced Data Quality
Better Security and Backup

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9
Q

Changes in data structure do not affect application programs.

A

Program-Data Independence

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10
Q

Reduces duplication of data.

A

Minimal Data Redundancy

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11
Q

Facilitates access to data across different applications.

A

Improved Data Sharing

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12
Q

Ensures accuracy and consistency of data.

A

Enhanced Data Quality

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13
Q

Provides mechanisms for data protection and recovery.

A

Better Security and Backup

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14
Q

Disadvantages of File Processing

A

Program-Data Dependence
Data Redundancy
Limited Data Sharing
Lengthy Development Times

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15
Q

Changes in data structure require changes in application programs.

A

Program-Data Dependence

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16
Q

Difficulty in accessing data across different systems.

A

Limited Data Sharing

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16
Q

Duplication of data across multiple files.

A

Data Redundancy

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17
Q

Increased time to develop and maintain systems.

A

Lengthy Development Times

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18
Q

Represents data and relationships in a graphical format.

A

Entity-Relationship Model

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18
Q

Evolution of Database Systems

A

Flat Files: 1960s - 1980s.
Hierarchical: 1970s - 1990s.
Network: 1970s - 1990s.
Relational: 1980s - Present.
Object-oriented: 1990s - Present.
Data Warehousing: 1980s - Present.

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19
Q

Organize data into rows and columns for easy retrieval and management.

A

Tables

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20
Q

is crucial for understanding how databases fit within larger information systems.

A

Information Systems Architecture (ISA)

21
Q

A data-oriented methodology to create and maintain information
systems

A

Information Engineering

22
Q

top-down planning approach (4)

A

Planning
Analysis
Design
Implementation.

23
Q

strategic planning factors (3)

A

Organization goals
Critical success factors
Problem areas.

24
Q

Corporate Planning Objects (5)

A

o Organizational units
o Organizational locations
o Business functions
o Entity types
o Information systems.

25
Q

The first step in database development specifies the scope and
general content

A

Enterprise Data Model

26
Q

Enterprise Data Model contents (4)

A

 Entity-relationship diagrams
 Descriptions of entity types
 Relationships between entities
 Business rules.

27
Q

The SDLC consists of several phases: (4)

A

o Project Identification and Selection
o Logical Design
o Physical Database Design
o Database Maintenance.

28
Q

SDLC stands for?

A

Systems Development Life Cycle

29
Q

Types of schemas (3)

A

o Physical Schema
o Conceptual Schema
o -External Schema

30
Q

User views.

A

External Schema

31
Q

Physical structures

A

Physical Schema

32
Q

ER models.

A

Conceptual Schema

33
Q

Involves analyzing requirements and developing a preliminary data
model.

A

Prototyping Methodology

34
Q

Key roles involved in database projects (5)

A

o Systems analysts
o Database analysts
o Users
o Programmers
o Database administrators.

35
Q

Shows time estimates of tasks.

A

Gantt Chart

35
Q

Displays dependencies between tasks.

A

PERT Chart

35
Q

Project Management Tools

A

Gantt Chart
PERT Chart

36
Q

Objects that have attributes and can have multiple instances in a database.

A

Entities

37
Q

Characteristics of an entity or relationship type.

A

Attributes

38
Q

Dependent on a strong entity and lacks a unique identifier.

A

Weak Entity

39
Q

Exists independently and has a unique identifier.

A

Strong Entity

39
Q

Associations between entities, which can also have attributes.

A

Relationships

40
Q

Attributes Types

A

Required vs. Optional Attribute
Simple vs. Composite Attributes
o Multivalued vs. Derived Attributes:

41
Q

Required must have a value; optional may not.

A

Required vs. Optional Attribute

41
Q

Composite attributes have meaningful parts.

A

Simple vs. Composite Attributes

42
Q

Modeling Relationships (3)

A

One-to-One
One-to-Many
Many-to-Many.

42
Q

Types of Relationships (3)

A

Unary
Binary
Ternary.

43
Q

Multivalued can take multiple values; derived values are calculated from other attributes.

A

Multivalued vs. Derived Attributes

44
Q

Defines the number of instances of one entity that can be associated with instances of another entity.

A

Cardinality

45
Q

Visual representations of entities, relationships, and attributes.

A

E-R Diagrams

46
Q

Used when a relationship needs attributes or when it has meaning independent of the entities it connects.

A

Associative Entities

47
Q

indicate when an event affecting a data value
occurred, useful for tracking changes over time.

A

Time-Stamping

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