Download Database

Mgt 20600:
IT Management & Applications
Databases
Tuesday
October 25, 2005
Reminders




Reading
– For today
 Strategies for Effective Data Storage and Management
– For next week
 Fundamentals text, Chapter 6, Information and Decision Support Systems
Homework
– Database homework due this Friday by 5pm
Exams
– Exam 1
 Nice work for many of you!
 If you didn’t do as well as you like, still many hundreds of points to go in the course
 Suggestions
– Always do reading ahead of time, not just before exam
– Always come to class
– Take the homeworks seriously and review them before the exams
– Come and see me and Christine for help with exam review
– Exam 2
 Tuesday, November 8th
 Covers networks and databases
– Homeworks 3 and 4
– Fundamentals text chapters 3 and 4
– Strategies for Effective Data Storage and Management online reading
– Lectures on networks and databases
 75 points
 Same kind of mix of questions as on first exam
In class next week: Decision Support Systems
Databases
A well-designed and well-managed
database is an extremely valuable tool in
supporting decision making
 Databases are key corporate assets
 Databases are the foundation for
sophisticated analyses that provide
business intelligence

– What new products to design
– How to market to particular customer groups
– Which customer groups are the most profitable
Traditional Approach
to Data Management
Traditional
approach: separate
data files are
created for each
application
Results in data
redundancy
(duplication)
Data
redundancy
conflicts with
data integrity
Database Approach
to Data Management
Database approach:
pool of related data is
shared by multiple
applications
Significant
advantages over
traditional
approach
Using Databases with Other
Software
 Database
management systems are
often used with other software
packages or the Internet
 A database management system can
act as a front-end application or a
back-end application
– Front-end application: interacts with
users
– Back-end application: interacts with
applications
Advantages of Database Approach
Improved strategic use of data
 Reduced data redundancy
 Improved data integrity
 Easier modification and updating
 Data and program independence
 Better access to data and information
 Standardization of data access
 A framework for program development
 Better overall protection of the data
 Shared data and information resources

Disadvantages of the
Database Approach
 More
complexity
 More difficult to recover from a
failure
 More expensive
Distributed Databases
 Distributed
database
– Data may be spread across several
smaller databases connected via
telecommunications devices
– Corporations get more flexibility in how
databases are organized and used
 Replicated
database
– Holds a duplicate set of frequently used
data
Databases
 Databases
must contain
– Accurate information
– Right kinds of information
– Current information
– Information from all organizational
functions
Database Data

Data regarding
– Important entities
 Customers
 Suppliers
 Transactions
– Each entity will have a number of attributes
about which you want to collect and store
information
 Customer
address
 Customer phone number
 Customer account number
Entities, Attributes, Keys
Entity: a generalized class of people,
places, or things (objects) for which
data is collected, stored, and
maintained (Table and records)
Attribute: a characteristic of an
entity (fields)
Data item: a value of an attribute
(fields)
Key: field(s) that identify a record
Primary key: field(s) that uniquely
identify a record
Hierarchy of Data
Field: name, number, or
characters that describe
an aspect of a business
object or activity
Record: a collection of
related data fields
File: a collection of
related records
Database: a collection of
integrated and related
files
Data Modeling and the
Relational Database Model
 When
building a database, consider:
– Content: What data should be collected,
at what cost?
– Access: What data should be provided
to which users, and when?
– Logical structure: How should data be
arranged to make sense to a given
user?
– Physical organization: Where should
data be physically located?
Data Modeling
 Building
a database requires two
types of design
– Logical design
 Shows
an abstract model of how data
should be structured and arranged to meet
an organization’s information needs
– Physical design
 Fine-tunes
the logical database design for
performance and cost considerations
Data Modeling
 Data
model: a diagram of data
entities and their relationships
 Entity-relationship (ER)
diagrams: data models that use
basic graphical symbols to show the
organization of and relationships
between data
Data Modeling
An Entity-Relationship (ER) Diagram for a
Customer Order Database
The Relational Database Model
Relational model: all data elements are
placed in two-dimensional tables
(relations), which are the logical
equivalent of files
 In the relational model:

– Each table represents a data entity
– Each row of a table represents a specific
instance of a data entity
– Columns of the table represent attributes
The Relational Database Model
A Relational Database Model
Manipulating Data
 Selecting:
eliminates rows
according to criteria
 Projecting: eliminates columns in a
table
 Joining: combines two or more
tables
 Linking: relates or links two or more
tables using common data attributes
Manipulating Data
Linking Data Tables to Answer an Inquiry
Database Management
Systems (DBMS)
 Interface
between
– Database and application programs
– Database and the user
 Database
types
– Flat file
– Single user
– Multiple users
Providing a User View
 Schema:
description of the entire
database
 User view: user-accessible portion
of the database
 Subschema
– Contains a description of a subset of the
database
– Identifies which users can view and
modify the data items in the subset
– Is used to create different user views
Providing a User View
The Use of Schemas and Subschemas
Creating and Modifying the
Database
 Data
definition language (DDL)
– Collection of instructions/commands that
define and describe data and data relationships
in a database
– Allows database creator to describe the data
and the data relationships that are to be
contained in the schema and the subschemas
 Data
dictionary:
a detailed description of
all the data used in the database
Creating and Modifying
the Database
A Typical Data Dictionary Entry
Storing and Retrieving Data
Logical and Physical Access Paths
Manipulating Data and
Generating Reports
Query-By-Example (QBE): a visual
approach to developing database queries
or requests
 Data manipulation language (DML):
commands that manipulate the data in a
database
 Structured Query Language (SQL):
ANSI standard query language for
relational databases
 Database programs can produce reports,
documents, and other outputs

Database Administration
 Database
administrator (DBA):
directs or performs all activities to
maintain a database environment
– Designing, implementing, and
maintaining the database system and
the DBMS
– Establishing policies and procedures
– Training employees
Selecting a Database
Management System
 Important
characteristics of
databases to consider:
– Size of the database
– Number of concurrent users
– Performance
– Ability to be integrated with other
systems
– Features of the DBMS
– Vendor considerations
– Cost of the system
Object-Oriented Database
Management Systems
 Object-oriented
database
– Stores both data and its processing
instructions
– Method: a procedure or action
– Message: a request to execute or run a
method
Object-Relational Database
Management Systems
 Object-relational
database
management system (ORDBMS)
– A DBMS capable of manipulating audio,
video, and graphical data
Data Warehouses, Data Marts,
and Data Mining
 Data
warehouse: collects business
information from many sources in
the enterprise
 Data mart: a subset of a data
warehouse
 Data mining: an informationanalysis tool for discovering patterns
and relationships in a data
warehouse or a data mart
Data Warehouses, Data Marts,
and Data Mining
Elements of a Data Warehouse
Data Warehouses, Data Marts,
and Data Mining
Common Data-Mining Applications
Online Analytical Processing
(OLAP)
 Software
that allows users to explore
data from a number of different
perspectives
Comparison of OLAP and Data Mining
Business Intelligence
 Business
intelligence (BI):
gathering the right information in a
timely manner and usable form and
analyzing it to have a positive impact
on business
 Knowledge management:
capturing a company’s collective
expertise and distributing it wherever
it can help produce the biggest
payoff