IM Prelim

Raw Data

Facts that have not yet been processed to reveal their meaning.

Information

The result of processing raw data to reveal its meaning.

Database

A shared, integrated computer structure that houses a collection of end-user data and metadata.

End-User Data

Raw facts of interest to the end user.

Metadata

Data about data, through which end-user data is integrated and managed.

DBMS

A collection of programs that manages the database structure and controls access to stored data.

Improved Data Sharing

DBMS serves as the intermediary between the user and the database.

Improved Data Security

Framework for enforcing data privacy and security policies.

Better Data Integration

Wider access to well-managed data promotes an integrated view of the organization.

Minimized Data Inconsistency

Exists when different versions of the same data appear in different places.

Improved Data Access

DBMS allows quick answers to ad hoc queries.

Improved Decision Making

Better-managed data leads to better information and decisions.

Increased End-User Productivity

Combines availability of data with tools for transforming data into usable information.

Single-User Database

A database that supports only one user at a time.

Desktop Database

A single user database that runs on a personal computer.

Multiuser Database

A database that supports multiple users simultaneously.

Workgroup Database

A database that supports a small number of users or a specific department.

Enterprise Database

A database used by the entire organization across many departments.

Centralized Database

A database that supports data located at a single site.

Distributed Database

A database that supports data distributed across several sites.

Cloud Database

A database created and maintained using cloud services.

General-Purpose Database

A database containing a variety of data for multiple disciplines.

Discipline-Specific Database

A database focused on specific subject areas.

Operational Database

A database designed for day-to-day operations.

Analytical Database

A database focused on historical data and business metrics.

Database Design

Activities focused on designing the database structure for end-user data.

Lengthy Development Times

Data retrieval tasks in file systems require extensive programming.

Difficulty Getting Quick Answers

Simple report generation requires complex programming for file systems.

Complex System Administration

Difficulties arise as the number of files increases.

Lack of Security and Limited Data Sharing

Faults found in file system repositories due to security issues.

Extensive Programming

Challenges in changing a file structure in a file system.

Structural Dependence

Change in database schema affects data access, requiring program changes.

Structural Independence

Changes in database schema do not affect data access.

Data Dependence

Data representation is dependent on physical data storage characteristics.

Data Independence

Data access is unaffected by changes in physical data storage.

Data Redundancy

Exists when the same data is stored unnecessarily in different places.

Poor Data Security

Multiple data copies increase unauthorized access risk.

Data Inconsistency

Conflicting versions of the same data appear in various locations.

Data-Entry Errors

More likely to occur with complex entries made in multiple files.

Data Integrity Problems

Data anomalies from entries that do not correspond to valid data.

Data Abnormality

An irregularity characterized by inconsistent changes made to a database.

Data Anomaly

Occurs when not all required changes in redundant data are made successfully.

Data Modeling

The process of creating a specific data model for a problem domain.

Entity

A person, place, thing, or event about which data will be collected.

Attribute

A characteristic of an entity.

Relationship

An association among entities.

One-to-One Relationship

A relationship where one entity is associated with one other entity.

One-to-Many Relationship

A relationship where one entity can be associated with multiple entities.

Many-to-Many Relationship

A relationship where multiple entities can be associated with multiple others.

Hierarchical Model

A data model represented by an upside-down tree structure.

Network Model

A data model developed to better represent complex relationships.

Schema

The conceptual organization of an entire database.

Subschema

Defines a portion of the database targeted by application programs.

Data Manipulation Language (DML)

Defines the environment for managing data.

Data Definition Language (DDL)

Allows the definition of schema components by a database administrator.

Relational Model

Introduced in 1970, representing a breakthrough in data management.

Entity Relationship Model

Graphical representation of entities and their relationships.

Object-Oriented Model

A model that represents data and relationships within an object.

Object

An abstraction of a real-world entity.

Attributes (in OODM)

Properties that describe an object's characteristics.

Classes

Collections of similar objects with shared structure and behavior.

Class Hierarchy

Organization of classes resembling an upside-down tree.

Inheritance

Ability of a class to inherit attributes from another class.

UML

A language based on Object-Oriented concepts for system modeling.

Extensible Markup Language (XML)

A metalanguage used to represent and manipulate data elements.

NoSQL

A movement to find better ways to manage large amounts of data.

Volume (in Big Data)

The total amount of data being stored.

Velocity (in Big Data)

The speed of data growth and processing requirements.

Variety (in Big Data)

The multiple formats of data being collected.

External Model

The user's view of the data environment.

Conceptual Model

Global view of the database by the entire organization.

Internal Model

Representation of the database as seen by the DBMS.

Internal Schema

Specific representation of an internal model.

Physical Model

Describes how data is saved on storage media.