Bahan Insisiasi 1minggu ke2 3 DBMS

(1)

Chapter 9

The Database and Database

Management System

(2)

Data Organization

 Data FieldData Field

– Smallest unit of data_{Smallest unit of data}

 RecordRecord

– _{Collection of related fields}_{Collection of related fields}

 FileFile

(3)

Data Organization (cont.)

 FoldersFolders

– Collection of related files_{Collection of related files}

– Conceptually similar to a branch of the tree_{Conceptually similar to a branch of the tree}

 SubfolderSubfolder

– _{A folder within a folder}_{A folder within a folder}

(4)

Organization of Data into

Folders

(5)

Common Models for

Organizing Data Files

1. Function

2. Frequency of Use 3. Users

(6)

Fundamental Building

Blocks for Database

Structures

(7)

Spreadsheet as a Simple

Database

 Rows and columns of a spreadsheet can be Rows and columns of a spreadsheet can be

regarded as a simple database regarded as a simple database

 Flat filesFlat files

– _{Does not have repeating columns}_{Does not have repeating columns}

– _{Spreadsheet table is a file and column is a field}_{Spreadsheet table is a file and column is a field}

 Key fieldsKey fields

(8)

Data Structure vs.

Spreadsheet Terminology

Spreadsheet Term Data Structure Term

Table File

Column Field

(9)

Database Structures

 DatabaseDatabase

– All data stored on computer-based resources of _{All data stored on computer-based resources of}

the organization

 Database Management System (DBMS)Database Management System (DBMS)

– _{Software application that stores the structure of}_{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

(10)

Database Structures

(cont.)

 Hierarchical structure Hierarchical structure

– Uses the ‘parent / children’ concept_{Uses the ‘parent / children’ concept}

– Limitation: Cannot handle ad hoc requests_{Limitation: Cannot handle ad hoc requests} – First DBMS was IDS by GE in 1964_{First DBMS was IDS by GE in 1964}

– _CODASYL_CODASYL

 Network structureNetwork structure

– Allow given record to point back to any other record in the _{Allow given record to point back to any other record in the}

database

– Specification released by CODASYL in 1971_{Specification released by CODASYL in 1971}

(11)

Database Structures

(cont.)

 Relational structureRelational structure

– Rows and columns_{Rows and columns}

– _{Frees designers from need to specify}_{Frees designers from need to specify}

relationships prior to building the database

relationships prior to building the database – Date and Codd described structure_{Date and Codd described structure}

(12)

Relational Database

Vendors

1. IBM

2. Informix Software, Inc. 3. Microsoft

(13)

The Database Concept

 Database conceptDatabase concept

– _{Logical integration of records in multiple files}_{Logical integration of records in multiple files}

 Data redundancyData redundancy

– _{Duplication of data}_{Duplication of data}

 Data inconsistencyData inconsistency

 Data independenceData independence

– Keep data specifications separate from programs, _{Keep data specifications separate from programs,}

in tables and indexes

(14)

Tables

Book Name Author Required Banking Principles Knox 25

(15)

Description of Book Table

(16)

Description of Student

Table

(17)

Table Relationships

(18)

Salesperson

(19)

Evolution of Database

Software

 GE’s IDS first exampleGE’s IDS first example

– Used with COBOL_{Used with COBOL}

 IBM’s IMSIBM’s IMS

– _{Apollo project}_{Apollo project}

 Interface IssuesInterface Issues

(20)

Evolution of Database

Software (cont.)

 SEQEL from IBMSEQEL from IBM

– _{Continuation of IMS}_{Continuation of IMS}

 Renamed SQLRenamed SQL

– Structured Query language _{Structured Query language}

– _{Embedded within traditional language}_{Embedded within traditional language} – Standalone_Standalone

(21)

Creating a Database

 Two approaches:Two approaches:

1. Process oriented approach

(problem-solving)

solving)

2.

(22)

Define

Defined by

(23)

Create

Data Needs Can Be Defined by

Creating an Enterprise

Model

(24)

Describing the Database

Contents

Data dictionary

Enter

dictionary data

Data description language (DDL) Step 1

(25)

Schema

 Data field nameData field name

 Aliases (other names used for same data Aliases (other names used for same data field)

field)

 Type of data (numeric alphabetic)Type of data (numeric alphabetic)

 Number of positionsNumber of positions

 Number of decimal positionsNumber of decimal positions

(26)

Rule for Required Field

(27)

Enforcing Value of

BookName

(28)

Creating a Database

 1) Describe the data1) Describe the data

 2) Enter the data2) Enter the data

 3) Use the database3) Use the database

– _{Query language}_{Query language} – _{Query-by-example}_{Query-by-example}

(29)

Query-by-Example

(30)

On-Line Analytical

Processing (OLAP)

 Feature to enable data analysis similar to Feature to enable data analysis similar to statistical cross-tabulation

statistical cross-tabulation

 Information can be generated from within Information can be generated from within DBMS

DBMS

(31)

Example OLAP Output

(32)

The Database

Administrator (DBA)

D B A Duties

 Database planning; work with users and Database planning; work with users and others, define schema, etc.

others, define schema, etc.

 Database implementation; creating the Database implementation; creating the database and enforcing policies and

database and enforcing policies and procedures

(33)

Data

Information InformationInformation

Transaction

statisticsstatistics

A DBMS

Model

(34)

Knowledge Discovery in

Databases (KDD)

 Data warehousingData warehousing

– _{refinement in the database concept to make it}_{refinement in the database concept to make it}

» very large_{very large} » very pure_{very pure}

» very retrievable_{very retrievable}

 Data martData mart

(35)

Knowledge Discovery in

Databases (KDD) (cont.)

 Data miningData mining

– the process of finding relationships in data _{the process of finding relationships in data}

that are unknown to the user

that are unknown to the user – _{may be for}_{may be for}

» _verification_verification » discovery_discovery

(36)

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

(37)

DBMS Advantages

 Reduce data redundancyReduce data redundancy

 Achieve data independenceAchieve data independence

 Enable integration of data from multiple Enable integration of data from multiple files

files

 Retrieve data and information quicklyRetrieve data and information quickly

(38)

DBMS Disadvantages

 Obtain expensive softwareObtain expensive software

 Obtain a large hardware configurationObtain a large hardware configuration

 Hire and maintain a DBA staffHire and maintain a DBA staff

(39)

Summary

 Organizations are storing vast amounts of dataOrganizations are storing vast amounts of data

 Organization and structures in databaseOrganization and structures in database

– _{Dominated by relational}_{Dominated by relational}

 Staff positionsStaff positions

– DBA_DBA

 Knowledge discovery in databasesKnowledge discovery in databases