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The Database and Database
Management System
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Data Organization
Data Field
Smallest unit of data
RecordCollection of related fields
File
Collection of related records
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Data Organization (cont.)
Folders
Collection of related files
Conceptually similar to a branch of the tree Subfolder
A folder within a folder
Movement of folders using GUI
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Organization of Data into Folders
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Common Models for
Organizing Data Files
1. Function
2. Frequency of Use3. Users
4. Projects
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Fundamental Building Blocks for
Database Structures
1. Data Value
2. Data Field3. Data Record
4. Data File
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Spreadsheet as a Simple
Database
Rows and columns of a spreadsheet can be
regarded as a simple database
Flat filesDoes not have repeating columns
Spreadsheet table is a file and column is a field
Key fieldsContains a value to uniquely identify each
record in a table
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Data Structure vs. Spreadsheet
Terminology
Spreadsheet Term Data Structure Term
Table File
Column Field
Row Record
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Database Structures
Database
All data stored on computer-based resources of
the organization Database Management System (DBMS)
Software application that stores the structure of
the database, the data itself, relationships
among the data in the database, as well as forms
and reports pertaining to the database
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Database Structures (cont.)
Hierarchical structure
Uses the parent / children concept
Limitation: Cannot handle ad hoc requests
First DBMS was IDS by GE in 1964
CODASYL
Network structure
Allow given record to point back to any other
record in the database
Specification released by CODASYL in 1971
Solves problem of having to backtrack through
data 9-10
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Database Structures (cont.)
Relational structure
Rows and columns
Frees designers from need to specifyrelationships prior to building the database
Date and Codd described structure
Does not rely on physical relationships
Easy to understand
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Relational Database Vendors
1. IBM
2. Informix Software, Inc.3. Microsoft
4. Oracle
5. Sybase
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The Database Concept
Database conceptLogical integration of records in multiple files
Data redundancy
Duplication of data
Data inconsistency
Data independence
Keep data specifications separate from
programs, in tables and indexes
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Tables
Book Name Author Required
Banking Principles Knox 25
Management Information Systems 8E McLeod and Schell 75
Personal Sales Techniques Wei 70
Quality Service, Quality Customer Brutus 54
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Description of Book Table
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Description of Student Table
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Table Relationships
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Salespersonfile
Salesstatistics
file
Customerfile
Accountsreceivable
file
Buyer
file
Inventory
file
Vendorfile
Accountspayable
file
Purchase
order
file
General
ledger
file
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Evolution of Database Software
GEs IDS first example
Used with COBOL
IBMs IMSApollo project
Interface Issues
Intels System 2000, RAMIS, IDMS, InquireQuery language interface
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Evolution of Database
Software (cont.)
SEQEL from IBM
Continuation of IMS
Renamed SQLStructured Query language
Embedded within traditional language
Standalone
PC database packages
dBase II
MS-Access9-20
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Creating a Database
Two approaches:
1. Process oriented approach (problem-solving)
2. Enterprise modeling
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Definethe Problem
Identify necessarydecisions
Describeinformation needs
Determine
the necessaryprocessing
Specifydata needs
1.
2.
3.
4.
5.
6.
Data Needs
Can BeDefined by
Taking a
Problem-
Oriented
Approach
DataSpecifications
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Create
enterprise
data model
Develop
Database
Database
2.
1.
Strategic Planning for Information Resources
Data Needs CanBe Defined by
Creating an
EnterpriseModel
Enterprise
Data Model
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Describing the Database Contents
Data dictionary
Enter
dictionary data
Data description
language (DDL)
Schema
Step 1
Step 2
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Schema
Data field name
Aliases (other names used for same data
field) Type of data (numeric alphabetic)
Number of positions
Number of decimal positions
Various integrity rules
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Rule for Required Field
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Enforcing Value of BookName
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Creating a Database
1) Describe the data
2) Enter the data
3) Use the databaseQuery language
Query-by-example
Data manipulation language (DML)
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Query-by-Example
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On-Line Analytical Processing
(OLAP)
Feature to enable data analysis similar to
statistical cross-tabulation
Information can be generated from withinDBMS
No need for separate statistical software
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Example OLAP Output
Marital Status
Married Single
Cash $752 $849
Payment Credit $1,277 $2,019
Method Check $283 $165
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The Database Administrator
(DBA)
D B A Duties
Database planning; work with users and
others, define schema, etc. Database implementation; creating the
database and enforcing policies and
procedures Database operations
Database security9-32
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Datadescriptionlanguageprocessor
Database manager
Querylanguage
Data manipulationlanguage (DML)
Application programs
Databasedescription(schema)
Database
Informationrequests
Information
Transactionlog
Backup/recoverymodule
Performancestatistics
Performancestatistics
processor
Performancestatistics
A DBMS
Model
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Knowledge Discovery in
Databases (KDD)
Data warehousing
refinement in the database concept to make it
very large very pure
very retrievable
Data mart
a more modest approach than data
warehousing, generally only one segment of
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Knowledge Discovery in
Databases (KDD) (cont.)
Data mining
the process of finding relationships in data
that are unknown to the user
may be for
verification
discovery combination of verification and discovery
9-35
Th K l d Di i
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The Knowledge Discovery in
Database (KDD) Process
1. Define the data and the task
2. Acquire the data
3. Clean the data
4. Develop the hypothesis and search model
5. Mine the data
6. Test and verify
7. Interpret and use
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DBMS Advantages
Reduce data redundancy
Achieve data independence
Enable integration of data from multiplefiles
Retrieve data and information quickly
Improve security
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DBMS Disadvantages
Obtain expensive software
Obtain a large hardware configuration Hire and maintain a DBA staff
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Requires a firm to:
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Summary
Organizations are storing vast amounts of
data
Organization and structures in database
Dominated by relational
Staff positions
DBA
Knowledge discovery in databases
Database management systems9-39