IM

Data

Raw 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, which integrates and manages end-user data.

DBMS (Database Management System)

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

Single-user database

A type of database that supports only one user at a time.

Desktop database

A single user database that runs on a personal computer.

Multiuser database

A type of database that supports multiple users at the same time.

Workgroup database

Supports a small number of users or a specific department within an organization.

Enterprise database

Used by the entire organization and supports many users across multiple departments.

Centralized database

Supports data located at a single site.

Distributed database

Supports data distributed across several different sites.

Cloud database

A database maintained using cloud services.

General-purpose database

Contains a wide variety of data used in multiple disciplines.

Discipline-specific database

Contains data focused on specific subject areas.

Operational database

Designed primarily to support a company's day-to-day operations.

Analytical database

Focused on storing historical data and business metrics for decision making.

Database design

Activities focused on the structure used to store and manage end-user data.

Data Modeling

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

Entity

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

Attribute

A characteristic of an entity.

Relationship

Describes an association among entities.

One-to-one relationship

A relationship type where one entity is related to exactly one other entity.

One-to-many relationship

A relationship type where one entity can relate to multiple entities.

Many-to-many relationship

A relationship type where multiple entities can relate to multiple entities.

Hierarchical Model

A data model developed in the 1960s represented by an upside-down tree structure.

Network Model

A data model created to represent complex data relationships effectively.

Relational Model

Introduced in 1970, it uses relations to represent data.

Entity Relationship Model

Graphical representation of entities and their relationships in a database.

Object-Oriented Model

Contains both data and its relationships in a single structure known as an object.

UML

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

XML

A metalanguage used to represent and manipulate data elements.

NoSQL

A movement to manage large amounts of data, focusing on performance and scalability.

Big Data characteristics

Volume, velocity, and variety refer to the size, speed, and format of data.

External Model

End user's view of the data environment.

Conceptual Model

A global view of the entire database for the organization.

Internal Model

Representation of the database as 'seen' by the DBMS.

Physical Model

Describes how data is saved on storage media.

Structural dependence

Change in database schema affects data access.

Structural independence

Changes in database schema do not affect data access.

Data dependence

Data representation depends on physical storage characteristics.

Data independence

Data access is unaffected by changes in physical storage characteristics.

Improved data sharing

DBMS serves as an intermediary between users and the database.

Improved data security

DBMS provides a framework for enforcing data privacy policies.

Better data integration

Wider access to well-managed data promotes an integrated organizational view.

Minimized data inconsistency

Reduces versions of the same data appearing in different locations.

Improved data access

DBMS enables quick responses to ad hoc queries.

Improved decision making

Better-managed data leads to better information and decision making.

Increased end-user productivity

Data availability combined with transformation tools enhances productivity.

Change management in database

Database changes should be managed to avoid complications.

DBMS Capabilities

Includes data storage, retrieval, and management functionalities.

Logical design transformation

Transforming logical design into a physical database layout.

Data Manipulation Language (DML)

Defines the environment for managing data.

Data Definition Language (DDL)

Allows the definition of schema components by the database administrator.

Database schema

The conceptual organization of the entire database.

Subschema

Defines a portion of the database for application programs.

Data Security Framework

Policies for protecting data from unauthorized access.

Database Design Pitfalls

Includes poor specifications and insufficient time for design.

Complex system administration

Difficulty managing increasing number of system files.

Extensive programming in file system

Challenges with data retrieval and updates in a file system.

Advantages of relational model

Simplifies data organization and management using relations.