Chapter 1 - Database Systems

Structural dependence

access to a file is dependent on its structure

General-purpose databases

contain a wide variety of data used in multiple disciplines

Discipline-specific databases

contain data focused on specific subject areas. The data in this type of database are used mainly for academic or research purposes within a small set of disciplines

Metadata

data about data, through which the end-user data are integrated and managed

Unstructured data

data that exist in their original (raw) state—that is, in the format in which they were collected

Business intelligence

describes a comprehensive approach to capture and process business data with the purpose of generating information to support business decision making

Data anomaly

develops when not all of the required changes in the redundant data are made successfully

Data inconsistency

exists when different versions of the same data appear in different places

Data redundancy

exists when the same data are stored unnecessarily at different places

Structural independence

exists when you can change the file structure without affecting the application's ability to access the data

Analytical database

focuses primarily on storing historical data and business metrics used exclusively for tactical or strategic decision making

NoSQL (Not only SQL)

generally used to describe a new generation of database management systems that is not based on the traditional relational database model designed to handle the unprecedented volume of data, variety of data types and structures, and velocity of data operations that are characteristic of these new business requirements

Semistructured data

have already been processed to some extent

Data processing (DP)

hired to create a computer-based system that would track data and produce required reports

Workgroup database

multiuser database which supports a relatively small number of users (usually fewer than 50) or a specific department within an organization

End-User Data

raw facts of interest to the end user

Database system

refers to an organization of components that define and regulate the collection, storage, management, and use of data within a database environment 5 Parts: Hardware, Software, People, Procedures, & Data

Database design

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

Performance tuning

relates to the activities that make the database perform more efficiently in terms of storage and access speed

Islands of information

scattered data locations

Multiuser database

supports multiple users at the same time

Single-user database

supports only one user at a time

XML database

supports the storage and management of semistructured XML data

Query result set

the answer to a query sent back by the DBMS

Knowledge

the body of information and facts about a specific subject

Structured Query Language (SQL)

the de facto query language and data access standard supported by the majority of DBMS vendors

Structured data

the result of formatting unstructured data to facilitate storage, use, and the generation of information

Information

the result of processing raw data to reveal its meaning

Enterprise database

when the database is used by the entire organization and supports many users (more than 50, usually hundreds) across many departments

Data integrity

• Data are accurate — there are no data inconsistencies • Data are verifiable — the data will always yield consistent results

Desktop database

a single-user database that runs on a personal computer

Extensible Markup Language (XML)

a special language used to represent and manipulate data elements in a textual format

Data warehouse

a specialized database that stores data in a format optimized for decision support

Query

a specific request issued to the DBMS for data manipulation—for example, to read or update the data

Ad hoc query

a spur-of-the-moment question

Data Dictionary

DBMS stores definitions of the data elements and their relationships (metadata) here

Data

Raw facts, such as a telephone number, a birth date, a customer name, and a year-to-date (YTD) sales value. Data have little meaning unless they have been organized in some logical manner. Data > Field > Record > File

database management system (DBMS)

a collection of programs that manages the database structure and controls access to the data stored in the database

Data Quality

a comprehensive approach to promoting the accuracy, validity, and timeliness of the data

Cloud database

a database that is created and maintained using cloud data services, such as Microsoft Azure or Amazon's AWS

Operational database also known as an online transaction processing (OLTP), transactional, or production database

a database that is designed primarily to support a company's day-to-day operations

Distributed database

a database that supports data distributed across several different sites

Centralized database

a database that supports data located at a single site

Data Management

a discipline that focuses on the proper generation, storage, and retrieval of data

Query language

a nonprocedural language — one that lets the user specify what must be done without having to specify how

Online analytical processing (OLAP)

a set of tools that work together to provide an advanced data analysis environment for retrieving, processing, and modeling data from the data warehouse

Database

a shared, integrated computer structure that stores a collection of the following: • End-user data • Metadata