INF2603
EXAM PACK
,Chapter 1 - Database Systems
Monday, 22 January 2018 20:32
1.2 Data Versus Information
Raw Data
Raw facts, or facts that have not yet been processed to reveal their meaning to the end user.
Information
The result of processing raw data to reveal its meaning. Information consists of transformed data
and facilitates decision making.
Knowledge
The body of information and facts about a specific subject. Knowledge implies familiarity, awareness
and understanding of information as it applies to an environment. A key characteristic is that new
knowledge can be derived from old knowledge.
1.3 Introducing the Database
Data Management
A process that focusses on data collection, storage and retrieval. Common data managements
functions include addition, deletion, modification and listing.
Database
A shared, integrated computer structure that houses a collection of data. A database contains two
types of data: end user data (raw data) and metadata.
Metadata
Data about data; that is, data about data characteristics and relationships.
Database Management System (RDBM)
The collection of programs that manages the database structure and controls access to the data
stored in the database.
DBMS Advantages
• Improved data sharing.
• Improved data security.
• Better data integration.
• Minimized data inconsistency.
• Improved data access.
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, • Improved data access.
• Improved decision making.
• Increased end-user productivity.
Data Inconsistency
A condition in which different versions of the same data yield different (inconsistent) results.
Query
A question or task asked by an end user of a database in the form of SQL code. A specific request for
data manipulation issued by the end user or the application to the DBMS.
Ad Hoc Query
A “spur-of-the-moment” question.
Query Result Set
The collection of data rows returned by a query.
Data Quality
A comprehensive approach to ensuring the accuracy, validity, and timeliness of data.
Types of Databases
• 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 concurrent users.
• Workgroup database - A multiuser database that usually supports fewer than 50 users or is
used for a specific department in an organization.
• Enterprise database - The overall company data representation, which provides support for
present and expected future needs.
• Centralized database - A database located at a single site.
• Distributed database - A logically related database that is stored in two or more physically
independent sites.
• Cloud database - A database that is created and maintained using cloud services, such as
Microsoft Azure o Amazon AWS.
• General-purpose database - A database that contains a wide variety of data used in multiple
disciplines.
• Discipline-specific database - A database that contains data focused on specific subject areas.
• Operation database - A database designed primarily to support a company’s day-to-day
operations. Also known as a transactional database, OLTP database, or production database.
• Analytic database - A database focused primarily on storing historical data and business
metrics used for tactical or strategic decision making.
Data Warehouse
A specialized database that stores historical and aggregated data in a format optimized for decision
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, A specialized database that stores historical and aggregated data in a format optimized for decision
support.
Online Analytical Processing (OLAP)
A set of tools that provide advanced data analysis for retrieving, processing, and modelling data
from the data warehouse.
Business Intelligence
A set of tools and processes used to capture, collect, integrate, store, and analyse data to support
business decision making.
Unstructured Data
Data that exists in its original, raw state; that is, in the format in which it was collected.
Structured Data
Data that has been formatted to facilitate storage, use, and information generation.
Semistructured Data
Data that has already been processed to some extent.
Extensible Markup Language (XML)
A metalanguage used to represent and manipulate data elements. Unlike other markup languages,
XML permits the manipulation of a document’s data elements. XML facilitates the exchange of
structured documents such as orders and invoices over the Internet.
XML Database
A database system that stores and manages semistructured XML data.
Social Media
Web and mobile technologies that enable “anywhere, anytime, always on” human interactions.
NoSQL
A new generation of database management systems that is not based on the traditional relational
database model.
1.4 Why Database design is important
UNISA Page 3
EXAM PACK
,Chapter 1 - Database Systems
Monday, 22 January 2018 20:32
1.2 Data Versus Information
Raw Data
Raw facts, or facts that have not yet been processed to reveal their meaning to the end user.
Information
The result of processing raw data to reveal its meaning. Information consists of transformed data
and facilitates decision making.
Knowledge
The body of information and facts about a specific subject. Knowledge implies familiarity, awareness
and understanding of information as it applies to an environment. A key characteristic is that new
knowledge can be derived from old knowledge.
1.3 Introducing the Database
Data Management
A process that focusses on data collection, storage and retrieval. Common data managements
functions include addition, deletion, modification and listing.
Database
A shared, integrated computer structure that houses a collection of data. A database contains two
types of data: end user data (raw data) and metadata.
Metadata
Data about data; that is, data about data characteristics and relationships.
Database Management System (RDBM)
The collection of programs that manages the database structure and controls access to the data
stored in the database.
DBMS Advantages
• Improved data sharing.
• Improved data security.
• Better data integration.
• Minimized data inconsistency.
• Improved data access.
UNISA Page 1
, • Improved data access.
• Improved decision making.
• Increased end-user productivity.
Data Inconsistency
A condition in which different versions of the same data yield different (inconsistent) results.
Query
A question or task asked by an end user of a database in the form of SQL code. A specific request for
data manipulation issued by the end user or the application to the DBMS.
Ad Hoc Query
A “spur-of-the-moment” question.
Query Result Set
The collection of data rows returned by a query.
Data Quality
A comprehensive approach to ensuring the accuracy, validity, and timeliness of data.
Types of Databases
• 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 concurrent users.
• Workgroup database - A multiuser database that usually supports fewer than 50 users or is
used for a specific department in an organization.
• Enterprise database - The overall company data representation, which provides support for
present and expected future needs.
• Centralized database - A database located at a single site.
• Distributed database - A logically related database that is stored in two or more physically
independent sites.
• Cloud database - A database that is created and maintained using cloud services, such as
Microsoft Azure o Amazon AWS.
• General-purpose database - A database that contains a wide variety of data used in multiple
disciplines.
• Discipline-specific database - A database that contains data focused on specific subject areas.
• Operation database - A database designed primarily to support a company’s day-to-day
operations. Also known as a transactional database, OLTP database, or production database.
• Analytic database - A database focused primarily on storing historical data and business
metrics used for tactical or strategic decision making.
Data Warehouse
A specialized database that stores historical and aggregated data in a format optimized for decision
UNISA Page 2
, A specialized database that stores historical and aggregated data in a format optimized for decision
support.
Online Analytical Processing (OLAP)
A set of tools that provide advanced data analysis for retrieving, processing, and modelling data
from the data warehouse.
Business Intelligence
A set of tools and processes used to capture, collect, integrate, store, and analyse data to support
business decision making.
Unstructured Data
Data that exists in its original, raw state; that is, in the format in which it was collected.
Structured Data
Data that has been formatted to facilitate storage, use, and information generation.
Semistructured Data
Data that has already been processed to some extent.
Extensible Markup Language (XML)
A metalanguage used to represent and manipulate data elements. Unlike other markup languages,
XML permits the manipulation of a document’s data elements. XML facilitates the exchange of
structured documents such as orders and invoices over the Internet.
XML Database
A database system that stores and manages semistructured XML data.
Social Media
Web and mobile technologies that enable “anywhere, anytime, always on” human interactions.
NoSQL
A new generation of database management systems that is not based on the traditional relational
database model.
1.4 Why Database design is important
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