Introduction to Database system

Introduction
DATABASE SYSTEM
putu.sundika@gmail.com

References : Database System Concepts (Abraham Silberschatz, Henry F. Korth, S. Sudarshan)

Database-System Applications
Enterprise Information
• Sales: For customer, product, and purchase information.
• Accounting: For payments, receipts, account balances, assets and other accounting
information.
• Human resources: For information about employees, salaries, payroll taxes, and benefits, and
for generation of paychecks.
• Manufacturing: For management of the supply chain and for tracking pro-duction of items in
factories, inventories of items in warehouses and stores,and orders for items.
• Online retailers: For sales data noted above plus online order tracking, generation of
recommendation lists, and maintenance of online product evaluations

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Database-System Applications
Banking and Finance
• Banking: customer information, accounts, loans, and banking transactions.
• Finance: For storing information about holdings, sales, and purchases of financial instruments
such as stocks and bonds; also for storing real-time market data to enable online trading by
customers and automated trading by the firm.
Universities: For student information, course registrations, and grades (inaddition to standard
enterprise information such as human resources and accounting)
Airlines: For reservations and schedule first to use databases in a geographica
Telecommunication: For keeping recordbills, maintaining balances on prepaid about the
communication networks.
Telecommunications: For keeping records of calls made, generating monthly bills, maintaining
balances on prepaid calling cards, and storing information about the communication networks

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Database on almost everyone’s life today

PAST
few direct
TODAY
most contact
contact to DB directly

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Database (past)
• Add new students, instructors, and courses
• Register students for courses and generate class rosters
• Assign grades to students, compute grade point averages (GPA), and
generate transcripts
• Create a new major
• etc

1960’s
Universities

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Disadvantages of File-Processing System
• Data redundancy and inconsistency
• Difficulty in accessing data
• Data isolation
• Integrity problems
• Atomicity problems
• Concurrent-access anomalies
• Security problems

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Data redundancy and inconsistency
Different programmers  different files and application different structures and the programs
in several programming languages  the same information may be duplicated in several places
(files).
For example : A student has a double major (music and mathematics). The address and
telephone number of that student may appear in a file that consists of student records of
students in the Music department and in a file that consists of student records of students in the
Mathematics department.
 This redundancy leads to higher storage and access cost.
 It may lead to data inconsistency  a changed student address may be reflected in the Music
department records but not elsewhere in the system.

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Difficulty in accessing data
“Find out the names of all students who live within a particular postal-code area “
Because no application program on hand to meet it, then :
1. either obtain the list of all students and extract the needed information manually or
2. ask a programmer to write the necessary application program.

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Data isolation
Because data are scattered in various files, and files may be in different formats, writing new
application programs to retrieve the appropriate data is difficult

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Integrity problems
The data values stored in the database must satisfy certain types of consistency constraints.
Suppose the university maintains an account for each department, and records the balance
amount in each account. Suppose also that the university requires that the account balance of a
department may never fall below zero. Developers enforce these constraints in the system by
adding appropriate code in the various application pro-grams. However, when new constraints
are added, it is difficult to change the programs to enforce them. The problem is compounded
when constraints involve several data items from different files.

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Atomicity problems
A computer system, like any other device, is subject to failure. In many applications, it is crucial
that, if a failure occurs, the data be restored to the consistent state that existed prior to the
failure.
Consider a program to transfer $500 from the account balance of department A to the account
balance of department B. If a system failure occurs during the execution of the program, it is
possible that the $500 was removed from the balance of department A but was not credited to
the balance of department B, resulting in an inconsistent database state. Clearly, it is essential to
database consistency that either both the credit and debit occur, or that neither occur.
That is, the funds transfer must be atomic—it must happen in its entirety or not at all. It is
difficult to ensure atomicity in a conventional file-processing system.

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Concurrent-access anomalies
Interaction of concurrent updates is possible and may result in inconsistent data.
Example : department A, with an account balance of $10,000. If two department clerks debit the
account balance (by say $500 and $100, respectively) of department A at almost exactly the
same time, the result of the concurrent executions may leave the budget in an incorrect (or
inconsistent) state.
Suppose that the programs executing on behalf of each withdrawal read the old balance, reduce
that value by the amount being withdrawn, and write the result back. If the two programs run
concurrently, they may both read the value $10,000, and write back $9500 and $9900,
respectively. Depending on which one writes the value last, the account balance of department A
may contain either $9500 or $9900, rather than the correct value of $9400.

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Security problems
Not every user of the database system should be able to access all the data.
For example, in a university, payroll personnel need to see only that part of the database that has
financial information. They do not need access to information about academic records. But, since
application programs are added to the file-processing system in an ad hoc manner, enforcing
such security constraints is difficult.

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View of Data
A major purpose of a database system is to provide users with an abstract view of the data.
That is, the system hides certain details of how the data are stored and maintained.

Level of Data Abstractions

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Level Data of Abstraction
type instructor=record
ID:char(5);
name:char(20);
deptname:char(20);
salary:numeric(8,2);
end;
another examples :
• Department  deptname:type, building:type, budget:type
• Course  coursed:type, title:type, deptname:type, credits:type
• Student  id:type,name:type,deptname:type, totcred:type

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Database Language
• Data-Definition Language (DDL)  to specify the database schema
• Data-Manipulation Language (DML)  is a language that enables users to access or
manipulate data as organized by the appropriate data model
In practice, the data-definition and data-manipulation languages are not two separate
languages; instead they simply form parts of a single database language, such as the widely used
SQL language
Data Models : a collection of conceptual tools for describing data, data relationships, data
semantics, and consistency constraints. A data model provides a way to describe the design of a
database at the physical, logical, and view levels.
Database Schema : overall design of the database  variable declarations

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Data-Manipulation Language (DML)
• Retrieval of information stored in the database
• Insertion of new information into the database
• Deletion of information from the database
• Modification of information stored in the database

 Procedural DMLs require a user to specify what data are needed and how to get those data.
 Declarative DMLs (also referred to as non procedural DMLs) require a user to specify what
data are needed without specifying how to get those data.

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Data-Definition Language (DDL)
 Data Storage and Definition language  database schema
Data stored in database must satisfy certain consistency constraint , ex: minus is disallowed for grade,
birth of date must less than 2000 etc

 Domain Constraints  possible values  integer types, character types, date/time types
 Referential Integrity  ensure that a value that appears in one relation
 Assertions  validation  database (domain dan referential integrity  special form of assertion)
 Authorization  read authorization, which allows reading, but not modification, of data. Insert
authorization, which allows insertion of new data, but not modification of existing data. Update
authorization, which allows modification, but not deletion, of data; and delete authorization,
which allows deletion of data.

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Sample of Relational Databases

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TUGAS KELOMPOK
 Rangkum materi hari ini dengan menggunakan kalimat sendiri
 (untuk setiap kelompok) Buatlah tabel-tabel yang menurut Anda kemungkinan digunakan pada :
1. Facebook
2. Google Plus
3. Gmail
4. Yahoo Mail
5. Blogspot.com
6. Wordpress.com
7. Google Earth
8. Google Drive
9. DropBox
10. Youtube.com
11. Kaskus.com

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Introduction to Database system

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Introduction to Database system