Database.pdf

Chapter 5 Data Resource
Management

Fundamental Data Concepts
● Characters
● Fields
● Records
● Databases

Characters
● Characters: The most basic logical data element is the character, which
consists of a single alphabetic, numeric, or other symbol.
● Each character is stored in a byte
● 1 byte contains 8 bits

Field
● Field: consists of a grouping of related characters
● A Data field represents an attribute (a characteristic or quality) of some entity
(object, person, place, or event).
● Ex. First Name, Last Name

Records
● Record: All of the fields used to capture, organize, and store the attributes of
an entity are grouped to form a record.
● A record represents a collection of attributes that describe a single instance of
an entity.
● Another way of looking at a record is that it represents a single instance of an
entity
● Every record should have a primary key, which is a unique field that is used to
identify a particular record or instance

Files
● Files: A group of related records is a data file
● When it is independent of any other files related to it, a single table may be
referred to as a flat file.
● Ex. Employee records, or payroll file

Databases
● Database: A database is an integrated collection of logically related data
elements.
● The data stored in a database are independent of the application programs
using them and of the type of storage devices on which they are stored
● Databases contain data elements describing entities and relationships among
entities

Entity Relationships
● Entities can be related to one another and describe each other’s properties
○ Unary Relationship: One type of entity is related to the same type of
entity
○ Binary Relationship: One type of entity is related to another type of
entity
● The number of times an entity of an entity set participates in a relationship
set is known as cardinality.

Entity Relationships - Cardinality
● Cardinality Types:
○ 1 to 1 One to One
○ 1 to N One to Many
○ N to 1 Many to One

Entity Relationships - Cardinality
● Cardinality Types:
○ N to M Many to Many

Database Structures
● The relationships among the many individual data elements stored in
databases are based on one of several logical data structures, or models.
● Five fundamental database structures are:
○ Hierarchical
○ Network
○ Relational
○ Object-oriented
○ Multidimensional models

Hierarchical Structure
● Used in early mainframe structures
● relationships between records form a hierarchy or tree like structure
● all records are dependent and arranged in multilevel structures, consisting of
one root record and any number of subordinate levels
● The data element or record at the highest level of the hierarchy is called the
root element.
● Data element can be accessed by moving progressively downward from a root
and along the branches of the tree until the desired record is located

Network Structure
● Represents more complex logical relationships and is still used by some
mainframe DBMS packages
● the network model can access a data element by following one of several
paths because any data element or record can be related to any number of
other data elements

Relational Structure
● The relational model is the most widely used of the three database structures.
It is used by most microcomputer DBMS packages, as well as by most
midrange and mainframe systems.
● All data elements within the database are viewed as being stored in the form
of simple two-dimensional tables, sometimes referred to as relations.
● The tables in a relational database are flat files that have rows and columns

Relational Structure
● Three basic operations can be performed on a relational database:
○ Select operation is used to create a subset of records that meet a stated
criterion.
○ Join operation can be used to combine two or more tables temporarily
so that a user can see relevant data in a form that looks like it is all in
one big table
○ Project operation is used to create a subset of the columns contained in
the temporary tables created by the select and join operations.

Multidimensional Structure
● Multidimensional model is a variation of the relational model that uses
multidimensional structures to organize data and express the relationships
between data
● Each cell within a multidimensional structure contains aggregated data
related to elements along each of its dimensions

Object Oriented Structure
● Object-oriented model is considered one of the key technologies of a new
generation of multimedia Web-based applications.
● An object consists of data values describing the attributes of an entity, plus
the operations that can be performed upon the data
● This encapsulation capability allows the object-oriented model to handle
complex types of data (graphics, pictures, voice, and text) more easily than
other database structures.

Object Oriented Structure
● The object-oriented model also supports inheritance.
● Inheritance allows new objects to be automatically created by replicating
some or all of the characteristics of one or more parent objects

Database Development
● Database administrators (DBAs) are responsible for database design and
maintenance
● Database developers use the data definition language (DDL) in database
management systems to develop and specify the data contents, relationships,
and structure of each database, as well as to modify these database
specifications when necessary
● Such information is cataloged and stored in a database of data definitions and
specifications called a data dictionary, or metadata repository

Database Development
● A data dictionary is a database management catalog or directory containing
metadata (i.e., data about data).
● Database administrators and database design analysts work with end users
and systems analysts to model business processes and the data they require.
● Then they determine:
1. What data definitions should be included in the database
2. What structures or relationships should exist among the data elements.

Data Planning and Database Design
1. Data Planning
a. Develop an enterprise model, showing business processes and need of
information among them
2. Requirements Specification
a. Identify the key data elements that are needed to perform their specific
business activities
3. Conceptual Design
a. High level design of information requirements
b. ERDs (Entity Relationship Diagrams)
4. Logical Design
a. Database schema

Data Planning and Database Design
5. Physical Design
a. Determining hardware/software requirements to implement the
database model

Database Schema
View Schema – the design of the database at the view level of the data
abstraction i.e how end users will use the schema
Logical Schema – the design of the database at the conceptual level of the
data abstraction
Physical Schema – the design of the database defined at the physical level of
data abstraction

Database Resource Management
● Data resource management is a managerial activity that applies information
systems technologies like database management, data warehousing, and
other data management tools to the task of managing an organization’s data
resources to meet the information needs of their business stakeholder

Types of Databases
● Operational Databases
Operational databases store detailed data needed to support the business
processes and operations of a company.
These databases focus on storing/retrieving information specific to the operations
of a business and do not usually include support function data.
Ex. customer database, inventory database

Types of Databases
● Distributed Databases
Distributed databases can reside on network servers on the World Wide Web, on
corporate intranets or extranets, or on other company networks.
Advantages:
Segregation of data allows for the protection of valuable information
Accommodates different storage requirements

Types of Databases
Disadvantages:
Maintaining Data accuracy across all database systems
Extra bandwidth & extra computing power needed to run the entire database

Types of Databases
Updating in a Distributed Database is done in 2 ways:
Replication: involves using a specialized software application that looks at each
distributed database and then finds the changes made to it.
Duplication: identifies one database as a master and then duplicates that database
at a prescribed time after hours so that each distributed location has the same
data, local changes to the database will not affect the overall state of the entire
database

Types of Databases
● External Databases
Third-party databases that can be used to retrieve information about a specific
domain or area of interest.
Can also include search engines

Types of Databases
● Hypermedia Databases
A type of database where the information is stored as a set of interconnected
multimedia pages on a Web site in a database of interrelated hypermedia
page elements, rather than interrelated data records.

Data Warehouse
A data warehouse stores data that have been extracted from the various
operational, external, and other databases of an organization. It is a central source
of the data that has been cleaned, transformed, and cataloged so that they can be
used by managers and other business professionals.
It is an enterprise system used for the analysis and reporting of structured and
semi-structured data from multiple sources.

Data Warehouse
Data warehouses may be subdivided into data marts, which hold subsets of data
from the warehouse that focus on specific aspects of a company, such as a
department or a business process.
Data in a data warehouse is static instead of dynamic, this restriction is so that
queries can be made on the data to look for complex patterns or historical trends
that might otherwise go unnoticed with dynamic data that change constantly as a
result of new transactions and updates

Data Mining
Data mining is a major use of data warehouse databases and the static data they contain.
In data mining, the data in a data warehouse are analyzed to reveal hidden patterns and
trends in historical business activity.
Many companies use data mining to:
• Perform market-basket analysis to identify new product bundles.
• Find root causes of quality or manufacturing problems.
• Prevent customer attrition and acquire new customers.
• Cross-sell to existing customers.
• Profile customers with more accuracy.

Traditional Data Processing
Challenges of Traditional Data Processing:
● The information is in several different files, each organized in a different way.
● Each file has been organized to be used by a different application program,
none of which produces the information needed.
● No application program was available to help get the information from these
files.

Problems of Traditional Data Processing:
● Data Redundancy: Independent data included a lot of duplicated data, and
updating it was quite cumbersome
● Lack of Data Integration: End users had to manually extract data from
required sources
● Data Dependence: Too much dependence on systems, changes in the data
and structure of the records required changes in the application programs
that used it

Problems of Traditional Data Processing:
● Lack of Data Integrity or Standardization: Attributes such as addresses,
phone numbers represented in different formats caused problem in data
integrity and data maintenance

Database Management System
To solve the problems of early file processing systems, Database Management
Systems (DBMS) were introduced
● A database management system (DBMS) is the main software tool of the
database management approach because it controls the creation,
maintenance, and use of the databases of an organization and its end user
● Ex. Microsoft Access, MySQL, MS SQL Server (RDBMS)

Main functions of a DBMS:
1. To create new databases and database applications
2. To maintain the quality of the data in an organization’s databases
3. To use the databases of an organization to provide the information that its
end users need.

Features of a DBMS
1. Database development involves defining and organizing the content,
relationships, and structure of the data needed to build a database.
2. Database application development involves using a DBMS to develop
prototypes of queries, forms, reports, and Web pages for a proposed business
application.
3. Database maintenance involves using transaction processing systems and
other tools to add, delete, update, and correct the data in a database.
4. Database interrogation involves asking for information from a database using
a query feature or a report generator

Database Interrogation & SQL
(Explained in Class)

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