Transcript Chapter 5 - Organizing Data and Information

Chapter 5
Organizing Data and
Information
ITEC 1010
Information and Organizations
Data
 Data
 A necessity for almost any enterprise to carry out its
business. Consists of raw facts, and when organized
may be transformed into information
 Database
 A collection of data organized to meet users’ needs
 Database management system (DBMS)
 A group of programs that manipulate the database and
provide an interface between the database and the user
of the database or other application programs
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DBMS ‘Discussion’ (1)
A collection of programs that enables you to store, modify, and
extract information from a database. There are many different types
of DBMSs, ranging from small systems that run on personal
computers to huge systems that run on mainframes. The following
are examples of database applications:

computerized library systems

automated teller machines

flight reservation systems

computerized parts inventory systems
From a technical standpoint, DBMSs can differ widely. The terms
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DBMS ‘Discussion’ (2)
relational, network, flat, and hierarchical all refer to the way a
DBMS organizes information internally. The internal organization can
affect how quickly and flexibly you can extract information.
Requests for information from a database are made in the form of a
query, which is a stylized question. For example, the query
SELECT ALL WHERE NAME = "SMITH" AND AGE > 35
requests all records in which the NAME field is SMITH and the AGE
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DBMS ‘Discussion’ (3)
field is greater than 35. The set of rules for constructing queries is
known as a query language. Different DBMSs support different query
languages, although there is a semi-standardized query language
called SQL (structured query language). Sophisticated languages for
managing database systems are called fourth-generation languages,
or 4GLs for short.
The information from a database can be presented in a variety of
formats. Most DBMSs include a report writer program that enables
you to output data in the form of a report. Many DBMSs also include
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DBMS ‘Discussion’ (4)
a graphics component that enables you to output information in the
form of graphs and charts.
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Hierarchy of Data
Schematic
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Hierarchy of data
Example
Personel file
Database
Department file
(Project database)
Payroll file
Files
005-10-6321 Johns Francine 10-7-65
549-77-1001 Buckley Bill 2-17-79
098-40-1370 Fiske Steven 1-5-85
Records
098-40-1370 Fiske Steven 1-5-85 598
Fields
Fiske
Characters
(bytes)
1000100
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(Last name field)
(Letter ‘F’ in ASCII)
Information and Organizations
(Personnel file)
(Record containing
SSN, last name,
first name, date of
hire)
Terminology
 Database
• A collection of integrated and related files
 File
• A collection of related records
 Record
• A collection of related fields
 Field
• A group of characters
 Character
• Basic building block of information, represented by a byte
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Information and Organizations
Data Entities, Attributes, and
Keys
 Entity
• A generalized class of people, places, or things (objects) for
which data are collected, stored, and maintained
• E.g., Customer, Employee
 Attribute
• A characteristic of an entity; something the entity is identified by
• E.g., Customer name, Employee name
 Keys
• A field or set of fields in a record that is used to identify the
record
• E.g, A field or set of fields that uniquely identifies the record
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Keys and Attributes
Employee #
Last name
First name
Hire date
Dept. #
005-10-6321
Johns
Francine
10-7-65
257
549-77-1001
Buckley
Bill
2-17-79
650
098-40-1370
Fiske
Steven
1-5-85
598
Key field
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Attributes (fields)
Information and Organizations
Entities
(records)
The Traditional Approach
 The traditional approach…
 Separate files are created and stored for each
application program
Schematic
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Information and Organizations
Data
Files
Application
programs
Users
Payroll
Payroll
programs
Reports
Invoicing
Invoicing
programs
Reports
Inventory
control
Inventory
control
programs
Reports
Management
inquiries
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Management
inquiries
programs
Information and Organizations
Reports
Drawbacks
 Data redundancy
 Duplication of data in separate files
 Lack of data integrity
 The degree to which the data in any one file is accurate
 Program-data dependence
 A situation in which program and data organized for
one application are incompatible with programs and
data organized differently for another application
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Database Approach
 The database approach…
 A pool of related data is shared by multiple
application programs
 Rather than having separate data files, each
application uses a collection of data that is
either joined or related in the database
Schematic
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Payroll
program
Reports
Inventory
program
Reports
Invoicing
program
Reports
Payroll data
Inventory
data
Invoicing
Data
Database
management
system
Other
data
Database
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Interface
Other
programs
Reports
Applications programs
Users
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Advantages









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Improved strategic use of corporate 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
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Disadvantages
 Relatively high cost of purchasing and
operating a DBMS in a mainframe operating
environment
 Increased cost of specialized staff
 Increased vulnerability
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Data Modeling and
Database Models (1)
 Planned data redundancy
 A way of organizing data in which the logical
database design is altered so that certain data
entities are combined
 Summary totals are carried in the data records
rather than calculated from elemental data
 Some data attributes are repeated in more than
one data entity to improve database
performance
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Data Modeling and
Database Models (2)
 Data model
 A map or diagram of entities and their relationships
 Enterprise data modeling
 Data modeling done at the level of the entire
organization
 Entity-relationship (ER) diagrams
 A data model that uses basic graphical symbols to
show the organization of and relationships between
data
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Example:
Entity Relationship (ER)
Diagram for a Customer
Ordering Database
Schematic
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Attributes
Last name
Colour
Entities
First
name
Customer
1
Order
N
Product
1:N one-to-many
relationship
Identification
number
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Identification
number
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Name
Hierarchical Database Model
 Hierarchical database model
 A data model in which data are organized in a
top-down, or inverted tree structure
Schematic
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Project 1
Department A
Employee
1
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Employee
2
Department B
Employee
3
Employee
4
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Department C
Employee
5
Employee
6
Network Data Model
 Network data model
• An expansion of the hierarchical database model
with an owner-member relationship in which a
member may have many owners
Project 1
Department A
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Project 2
Department B
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Department C
Relational Data Model
 Relational data model
 All data elements are placed in twodimensional tables, called relations, that are
the logical equivalent of files
Schematic
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Data Table 2: Department Table
Data Table 1: Project Table
Project Number
Description
Dept. Number
Dept. Number
Dept. Name
Manager SSN
155
Payroll
257
257
Accounting
421-55-99993
498
Widgets
632
632
Manufacturing
765-00-3192
226
Sales manager
598
598
Marketing
098-40-1370
Data Table 3: Manager Table
SSN
Last Name
First Name
Hire Date
Dept. Number
005-10-6321
Johns
Francine
10-7-65
257
549-77-1001
Buckley
Bill
2-17-79
650
098-40-1370
Fiske
Steven
1-5-85
598
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Relational Database Terminology
 Selecting
 Data manipulation that eliminates rows according to
certain criteria
 Projecting
 Data manipulation that eliminates columns in a table
 Joining
 Data manipulation that combines two or more tables
 Linked
 Relating tables in a relational database together
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Linking Data Tables to Answer
an Inquiry
Schematic
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Project Number
Description
Dept. Number
155
Payroll
257
498
Widgets
632
226
Sales manager
598
Dept. Number
Dept. Name
Manager SSN
257
Accounting
421-55-99993
632
Manufacturing
765-00-3192
598
Marketing
098-40-1370
SSN
Last Name
First Name
005-10-6321
Johns
Francine
10-7-65
257
549-77-1001
Buckley
Bill
2-17-79
650
098-40-1370
Fiske
Steven
1-5-85
598
Information and Organizations
Hire Date Dept. Number
Building and Modifying a
Relational Database
 Using Microsoft Access
Screen snap
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Schemas and Subschemas
 Schema
 A description of the entire database
 Subschema
 A file that contains a description of a subset of
the database and identifies which users can
perform modifications on the data items in that
subset
Schematic
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DBMS
Schema
Subschema
A
User
1
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Subschema
B
User
2
User
3
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Subschema
C
User
4
User
5
Schema ‘Discussion’
Pronounced skee-ma, the structure of a database system, described
in a formal language supported by the database management
system (DBMS). In a relational database, the schema defines the
tables, the fields in each table, and the relationships between fields
and tables.
Schemas are generally stored in a data dictionary. Although a
schema is defined in text database language, the term is often used
to refer to a graphical depiction of the database structure.
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Data Definition Language
 Data Definition Language (DDL)
 A collection of instructions and commands
used to define and describe data and data
relationships in a specific database
Schematic
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SCHEMA DESCRIPTION
SCHEMA NAME IS XXXX
AUTHOR
XXXX
DATE
XXXX
FILE DESCRIPTION
FILE NAME IS XXXX
ASSIGN XXXX
FILE NAME IS XXXX
ASSIGN XXXX
AREA DESCRIPTION
AREA NAME IS XXXX
RECORD DESCRIPTION
RECORD NAME ISXXXX
RECORD ID IS XXXX
LOCATION MODE ISXXXX
WITHIN XXX AREA FROM XXXX THRU XXXX
SET DESCRIPTION
SET NAME IS XXXX
ORDER IS XXXX
MODE IS XXXX
MEMBER IS XXXX
.
.
.
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Data Dictionary
 Data Dictionary
 A detailed description of all data used in the
database
Schematic
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NORTHWESTERN MANUFACTURING
PREPARED BY:
DATE:
APPROVED BY:
VERSION:
PAGE:
D. BORDWELL
04 AUGUST
J. EDWARDS
3.1
1 OF 1
DATA ELEMENT NAME:
DESCRIPTION:
OTHER NAMES:
VALUE RANGE:
DATA TYPE:
POSITIONS:
PARTNO
INVENTORY PART NUMER
PTNO
100 TO 5000
NUMERIC
4 POSITIONS OR COLUMNS
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DATE:
Information and Organizations
13 OCTOBER
Data Dictionary Features
 Provide a standard definition of terms and data
elements
 Assist programmers in designing and writing
programs
 Simplify database modification
 Reduce data redundancy
 Increase data reliability
 Faster program development
 Easier modification of data and information
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Logical and Physical
Access Paths
 Logical access path (LAP)
 Application requires information from the
DBMS
 Physical access path (PAP)
 DBMS accesses a storage device to retrieve
data
Schematic
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Data
on
storage
devices
Physical access path (PAP)
DBMS
Logical access path (LAP)
Management
inquiries
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Other
software
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Application
programs
Manipulating Data
 Concurrency control
 A method of dealing with a situation in which two or
more people need to access the same record in a
database at the same time
 Data manipulation language (DML)
 The commands that are used to manipulate the data in
a database
 Structured query language (SQL)
 A standardized data manipulation language
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Structured Query Language (SQL)
 “Invented” at IBM’s Almaden Research
Centre (San Jose, CA) in the 1970s
 E.g.,
SELECT * FROM EMPLOYEE WHERE
JOB_CLASSIFICATION = “C2”
Select all (“*”) columns from the EMPLOYEE
table in which the JOB_CLASSIFICATION field
is equal to “C2”
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SQL ‘Discussion’ (1)
Abbreviation of structured query language, and pronounced either
see-kwell or as separate letters. SQL is a standardized query
language for requesting information from a database. The original
version called SEQUEL (structured English query language) was
designed by an IBM research center in 1974 and 1975. SQL was first
introduced as a commercial database system in 1979 by Oracle
Corporation.
Historically, SQL has been the favorite query language for database
management systems running on minicomputers and mainframes.
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SQL ‘Discussion’ (2)
Increasingly, however, SQL is being supported by PC database
systems because it supports distributed databases (databases that
are spread out over several computer systems). This enables
several users on a local-area network to access the same database
simultaneously.
Although there are different dialects of SQL, it is nevertheless the
closest thing to a standard query language that currently exists. In
1986, ANSI approved a rudimentary version of SQL as the official
standard, but most versions of SQL since then have included many
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SQL ‘Discussion’ (3)
extensions to the ANSI standard. In 1991, ANSI updated the
standard. The new standard is known as SAG SQL.
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Database Output
Screen snap
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Popular Database Management
Systems for End Users




Microsoft Access 98
Lotus Approach 98
Inprise (formerly Borland) dBASE
DBMS Selection Criteria
•
•
•
•
•
•
•
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Database size
Number of concurrent users
Performance
Integration
Features
The vendor
Cost
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Distributed Databases
 Distributed database…
 A database in which the actual data may be
spread across several smaller databases
connected via telecommunications devices
‘Pretty’ picture
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Data Warehouse
 Data warehouse
 A relational database management system designed
specifically to support management decision making
Current evolution of Decision Support Systems (DSSs)

 Data mart
 A subset of a data warehouse for small and mediumsize businesses or departments within larger
companies
Schematic
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Relational
databases
Data
extraction
process
Hierarchical
databases
Network
databases
Data
cleanup
process
Flat files
Spreadsheets
End user access
Data
wharehouse
Query and
analysis
tools
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Designing a Customer Data Warehouse
 Sharply define your goals and objectives
before you build the warehouse
 Choose the software that best fits your goals
 Determine who/what should be in the database
 Develop a plan
 Measure results
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Data Mining Applications
 Data mining
 The automated discovery of patterns and relationships
in a data warehouse
 Data mining applications
•
•
•
•
•
•
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Market segmentation
Customer queries
Fraud detection
Direct marketing
Market basket analysis
Trend analysis
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On-Line Analytical
Processing (OLAP)
 On-line analytic processing (OLAP)
• Access to multidimensional databases providing
•
managerially useful display techniques
Now used to store and deliver data warehouse
information
 Data warehouse and OLAP
• Provides top-down, query-driven analysis
 Data mining
• Provides bottom-up, discovery-driven analysis
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Open Database
Connectivity (ODBC)
 Open database connectivity (ODBC)
• A set of standards that ensures software written to
comply with these standards can be used with any
ODBC-compliant database
Schematic
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dBASE
ODBC Import
ACCESS
database
ODBC Export
ODBC Link
Lotus 1-2-3
spreadsheet
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Paradox
database
Object-Relational Database Management
Systems (ORDBMS)
 Object-relational database management system (ORDBMS)

• A DBMS capable of manipulating audio, video, and graphical data.
Hypertext
• Users can search and manipulate alphanumeric data in an
unstructured way
 Hypermedia
• Allows businesses to search and manipulate multimedia forms of
data
 Spatial data technology
• Use of an object-relational database to store and access data
according to the location it describes and to permit spatial queries
and analysis
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End of Chapter 5
Chapter 6
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