Understanding Data, Information, and Databases

Data

Data consists of raw facts.

Raw Data

The word raw indicates that the facts have not yet been processed to reveal their meaning.

Information

Information is the result of processing raw data to reveal its meaning.

Information

Information can be used as the foundation for decision making.

FILE

A collection of related records.

Data Processing

Data processing can be as simple as organizing data to reveal patterns or as complex as making forecasts or drawing inferences using statistical modeling.

Context

To reveal meaning, information requires context.

Knowledge

Knowledge implies familiarity, awareness, and understanding of information as it applies to an environment.

Database

A database is a shared, integrated computer structure that stores a collection of data and metadata.

End-user Data

End-user data or data—that is, raw facts of interest to the end user.

Metadata

The metadata describes the data characteristics and the set of relationships that links the data found within the database.

Database Design

It refers to the activities that focus on the design of the database structure that will be used to store and manage end-user data.

DATA

Raw facts, such as a telephone number, a birth date, a customer name, and a year-to-date (ytd) sales value.

FIELD

A character or group of characters (alphabetic or numeric) that has a specific meaning.

RECORD

A logically connected set of one or more fields that describes a person, place, or thing.

Business Rules

A business rule is a brief, precise, and unambiguous description of a policy, procedure, or principle within a specific organization.

Business Rules

Business rules set the stage for the proper identification of entities, attributes, relationships, and constraints.

Relational Database

A table is perceived as a two-dimensional structure composed of rows and columns.

Relational Database

Each table row (tuple) represents a single entity occurrence within the entity set.

Relational Database

Each table column represents an attribute, and each column has a distinct name.

Relational Database

Each intersection of a row and column represents a single data value.

Relational Database

All values in a column must conform to the same data format.

Relational Database

Each column has a specific range of values known as the attribute domain.

Relational Database

The order of the rows and columns is immaterial to the DBMS.

Relational Database

Each table must have an attribute or combination of attributes that uniquely identifies each row.

Keys or Superkeys

In the relational model, keys are important because they are used to ensure that each row in a table is uniquely identifiable.

Key

A key consists of one or more attributes that determine other attributes.

Composite Key

A composite key is a key that is composed of more than one attribute.

Candidate Key

A candidate key is a minimal superkey—that is, a superkey without any unnecessary attributes.

Primary Key (PK)

The primary key (PK) is the candidate key chosen to be the primary means by which the rows of the table are uniquely identified.

Entity integrity

is the condition in which each row (entity instance) in the table has its own unique identity.

Foreign key (fK)

is the primary key of one table that has been placed into another table to create a common attribute.

Entity

is an object of interest to the end user.

Attributes

are characteristics of entities.

Required attribute

is an attribute that must have a value; in other words, it cannot be left empty.

Optional attribute

is an attribute that does not require a value; therefore, it can be left empty.

Composite attribute

is an attribute that can be further subdivided to yield additional attributes.

Simple attribute

is an attribute that cannot be subdivided.

Single-Valued Attributes

is an attribute that can have only a single value.

Multivalued Attributes

are attributes that can have many values.

Derived Attributes

need not be physically stored within the database; instead, it can be derived by using an algorithm.

Cardinality

expresses the minimum and maximum number of entity occurrences associated with one occurrence of the related entity.

SQL

is a database language that allows you to create database and table structures, perform basic data management chores (add, delete, and modify), and perform complex queries designed to transform the raw data into useful information.

Data Manipulation Language (DML)

includes commands to insert, update, delete, and retrieve data within the database tables.

Data Definition Language (DDL)

includes commands to create database objects such as tables, indexes, and views, as well as commands to define access rights to those database objects.

Transaction Control Language (TCL)

is a logical unit of work composed of one or more SQL statements, as defined by business rules.

Data Control Language (DCL)

is used to control access to data objects, such as giving a user permission to only view the PRODUCT table, and giving another user permission to change the data in the PRODUCT table.

Character data

is composed of any printable characters such as alphabetic values, digits, punctuation, and special characters.

Numeric data

is composed of digits, such that the data has a specific numeric value.

Date data

is composed of date and, occasionally, time values.

SELECT

specifies the attributes to be returned by the query.

FROM

specifies the table(s) from which the data will be retrieved.

WHERE

filters the rows of data based on provided criteria.

GROUP BY

groups the rows of data into collections based on sharing the same values in one or more attributes.

HAVING

filters the groups formed in the GROUP BY clause based on provided criteria.

ORDER BY

sorts the final query result rows in ascending or descending order based on the values of one or more attributes.