ielm 511: information system design

IELM 511: Information System design

Introduction

Part 1. ISD for well structured data – relational and other DBMS

ISD for systems with non-uniformly structured data

Part III: (one out of)

Basics of web-based IS (www, web2.0, …)Markup’s, HTML, XMLDesign tools for Info Sys: UML

API’s for mobile appsSecurity, CryptographyIS product lifecyclesAlgorithm analysis, P, NP, NPC

Info storage (modeling, normalization)Info retrieval (Relational algebra, Calculus, SQL)DB integrated API’s

Agenda

Structured Query Language (SQL)

DB API’s

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Recall our Bank DB design

BRANCH( b_name, city, assets)

CUSTOMER( cssn, c_name, street, city, banker, banker_type)

LOAN( l_no, amount, br_name)

PAYMENT( l_no, pay_no, date, amount)

EMPLOYEE( e_ssn, e-name, tel, start_date, mgr_ssn)

ACCOUNT( ac_no, balance)

SACCOUNT( ac_no, int_rate)

CACCOUNT( ac_no, od_amt)

BORROWS( cust_ssn, loan_num)

DEPOSIT( c_ssn, ac_num, access_date)

DEPENDENT( emp_ssn, dep_name)

Background: Structured Query Language

Basics of SQL:

A DataBase Management System is an IT system

Core requirements: - A structured way to store the definition of data [why ?] DDL - Manipulation of data [obviously!] DML

SQL: a combined DDL+DML

SQL as a DDL

A critical element of any design is to store the definitions of its components.

In DB design, we deal with tables, using table names, attribute names etc.Each of these terms should have unambiguous syntax and semantics.

A systematic way to specify and store these meta-data is by the use of aData Definition Language

The information about the data is stored in a Data Dictionary

SQL provides a unified DDL + a Data Manipulation Language (DML).

SQL as a DDL: create command

To create a new database:

create database my_database;

To create a new table:

create table my_table (attribute_name attribute_type constraint,….,constraint, …

);

To create an index on a table:

create index my_index on my_table( attribute);

A DB stores one or more tablesand one or more indexes

A table stores data

An index is a special filefor faster DB look-up,when searching the specifiedtable for some data usingthe specified attribute.

SQL as a DDL: create command examples

create database bank;

create table loan ( l_no char(10), amount double, br_name char(30) references branch(b_name), primary key (loan_number));

BORROWS( cust_ssn, loan_num)

create table borrows ( cust_ssn char(11), loan_num char(10), primary key (cust_ssn, loan_num), constraint borrows_c1 foreign key cust_ssn references customer( cssn), constraint borrows_c2 foreign key loan_num references loan( l_no));

LOAN( l_no, amount, br_name)

Note on metadata: system catalogs

Metadata = data about data.

DBMS manages a ‘data dictionary’ sometimes called ‘system catalog’ with

- When was the DB and each table created/modified - Name of each attribute, its data type, and comments describing it, - List of all users who can access the DB and their passwords, - Which user can do what (read/add/update/delete/authorize) to the data.

System catalog itself is stored in a table, and users can see (if theyhave authority) the data in it.

SQL as a DML: insert, drop commands

To add one row into a table:

insert into branch values( “Downtown”, “Brooklyn”, 9000000);

insert into loan values( “L17”, 1000, “Downtown”);

To remove an entire table from the DB:

drop table branch;

Sequence in which you execute ‘insert’ matters !This insert will fail unless table ‘branch’ has a row with ‘Downtown’

Note: this ‘drop’ command will fail if, e.g. there is data in table ‘loan’ [why?]

Note: char( ), date, datetime types: data must be “quoted” integer, single, double (number data types) are not quoted.

SQL as a DML: select command

To get some data from a ( set of ) table (s):

select attribute1, …, attribute_nfrom table_1, …, table_mwhere selection_or_join_condition1, …, selection_or_join_condition_rgroup by attribute_ihaving aggregate_function( attribute_j, … )order by attribute_kO

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nal

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uire

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SQL as a DML: select command

select customer, loan_nofrom borrows;

customer loan_no

111-12-0000 L17

222-12-0000 L23

333-12-0000 L15

444-00-0000 L93

666-12-0000 L17

111-12-0000 L11

999-12-0000 L17

777-12-0000 L16

To get some data from a ( set of ) table (s)

select customer as “customer ssn”from borrows; customer ssn

111-12-0000

222-12-0000

333-12-0000

444-00-0000

666-12-0000

111-12-0000

999-12-0000

777-12-0000

select * from borrows;

Notes:* is a wildcardas: gives alias name to attribute

select distinct loan_nofrom borrows;

loan_no

L17

L23

L15

L93

L11

L16

SQL select: row filters

select distinct branch_namefrom loanwhere amount > 1200

Example: Find the names of all branches that have given loans larger than 1200

branch_name

Redwood

Pennyridge

Note: all operations in ‘where’are applied one row at a time

loan_number amount branch_name

L17 1000 Downtown

L23 2000 Redwood

L15 1500 Pennyridge

L93 500 Mianus

L11 900 Round Hill

L16 1300 Pennyridge

LOAN

SQL select: joins

select customer, loan.*from borrows, loanwhere loan_no = loan_number and amount > 1200

-condition for join of loan, borrows

selection condition

Example: Find the customer ssn, loan no, amount and branch name for all loans > 1200

customer loan_number amount branch_name

222-12-0000 L23 2000 Redwood

333-12-0000 L15 1500 Pennyridge

777-12-0000 L16 1300 Pennyridge

WHERE clause:multiple -conditions and, or, notcomparing cell values: >, =, !=, <, etc.

BORROWS

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

LOAN

Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17

branch_nameamountloan_number

Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


SQL select: joins with table and column aliases

select E.e_name as worker, M.e_name as bossfrom employee as E, employee as Mwhere E.mgr_ssn = M.e_ssn

Note:

E, M are aliases (copies) of employee table

Example: Find the names of employees and their manager.

worker boss

Jones Adams

Smith Jones

Lee Jones

Turner Adams

Jones Chan

Chan Black

Adams Black

Black null

E = M

888-99-9999Mar-199587621Jones987-65-4321

777-77-7777Feb-198087654Chan888-99-9999

99111

77777

55555

54321

54321

12345

tel

Jan-1980

Feb-1990

Aug-2002

Mar-1998

Mar-1998

Nov-2005

start_date

nullBlack777-77-7777

321-32-4321

555-66-8888

123-45-6789

333-11-4444

111-22-3333

e_ssn

777-77-7777Adams

321-32-4321Turner

111-22-3333Lee

111-22-3333Smith

321-32-4321Jones

mgr_ssne_name

888-99-9999Mar-199587621Jones987-65-4321

777-77-7777Feb-198087654Chan888-99-9999

99111

77777

55555

54321

54321

12345

tel

Jan-1980

Feb-1990

Aug-2002

Mar-1998

Mar-1998

Nov-2005

start_date

nullBlack777-77-7777

321-32-4321

555-66-8888

123-45-6789

333-11-4444

111-22-3333

e_ssn

777-77-7777Adams

321-32-4321Turner

111-22-3333Lee

111-22-3333Smith

321-32-4321Jones

mgr_ssne_name

SQL select: nested queries, in

select c_ssnfrom depositwhere c_ssn in ( select customer

from borrows)Notes:‘in’ performs a set membership test

Example: Find ssn of customers who have both deposit and loan

c_ssn

222-12-0000

333-12-0000

111-12-0000

BORROWS

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_noDEPOSIT

Mar 1, 09A217111-12-0000

Feb 25, 09A101000-12-0000

888-12-0000

555-00-0000

333-12-0000

222-12-0000

888-12-0000

c_ssn

Mar 1, 98A201

Mar 10, 09A305

Feb 28, 09A102

Feb 1, 09A215

Jan 1, 09A101

accessDateac_num

Mar 1, 09A217111-12-0000

Feb 25, 09A101000-12-0000

888-12-0000

555-00-0000

333-12-0000

222-12-0000

888-12-0000

c_ssn

Mar 1, 98A201

Mar 10, 09A305

Feb 28, 09A102

Feb 1, 09A215

Jan 1, 09A101

accessDateac_num

SQL select: nested queries, in

select c_ssnfrom depositwhere c_ssn not in ( select customer

from borrows)

Notes:‘not in’ is true if ‘in’ is false.

Example: Find ssn of customers who have a deposit but no loan

c_ssn

888-12-0000

555-00-0000

888-12-0000

000-12-0000

BORROWS

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_noDEPOSIT

Mar 1, 09A217111-12-0000

Feb 25, 09A101000-12-0000

888-12-0000

555-00-0000

333-12-0000

222-12-0000

888-12-0000

c_ssn

Mar 1, 98A201

Mar 10, 09A305

Feb 28, 09A102

Feb 1, 09A215

Jan 1, 09A101

accessDateac_num

Mar 1, 09A217111-12-0000

Feb 25, 09A101000-12-0000

888-12-0000

555-00-0000

333-12-0000

222-12-0000

888-12-0000

c_ssn

Mar 1, 98A201

Mar 10, 09A305

Feb 28, 09A102

Feb 1, 09A215

Jan 1, 09A101

accessDateac_num

SQL select: nested, correlated queries, exists

select branch_namefrom branchwhere not exists (select *

from loanwhere branch.branch_name = loan.branch_name)

1. Correlated: ‘where’ clause of inner query refers to outer query2. ‘exists’ is true is there is >= 1 row in evaluating inner query; ‘not exists’ is true is ‘exists’ is false

Existential qualifier (a generalization of ‘in’)

Example: Find the names of branches that have given no loan

LOAN

Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


BRANCH

300000BenningtonPownal

3700000RyeNorth Town

7100000BrooklynBrighton

Round Hill

Mianus

Pennyridge

Redwood

Downtown

branch_name

8000000Horseneck

400000Horseneck

1700000Horseneck

2100000Palo Alto

9000000Brooklyn

assetscity




Round Hill

Mianus

Pennyridge

Redwood

Downtown

branch_name

8000000Horseneck

400000Horseneck

1700000Horseneck

2100000Palo Alto

9000000Brooklyn

assetscity

SQL select: arithmetic operations on columns

select branch_name, assets*0.000001 as “assets (m)”from branch

Notes: arithmetic ops can be used in SELECT, WHERE, HAVING

Report the branch name and assets in units of millions BRANCH




Round Hill

Mianus

Pennyridge

Redwood

Downtown

branch_name

8000000Horseneck

400000Horseneck

1700000Horseneck

2100000Palo Alto

9000000Brooklyn

assetscity




Round Hill

Mianus

Pennyridge

Redwood

Downtown

branch_name

8000000Horseneck

400000Horseneck

1700000Horseneck

2100000Palo Alto

9000000Brooklyn

assetscity

branch_name assets (m)

Downtown 9.0

Redwood 2.1

Pennyridge 1.7

Mianus 0.4

Round Hill 8.0

Pownal 0.3

North Town 3.7

Brighton 7.1

select branch_name, avg( amount) as Avg, max( amount) as Max, count( branch_name) as no_loansfrom loangroup by branch_nameorder by no_loans desc

SQL select: group by, group-wise aggregation functions

1. Aggregating functions: avg, max, min, sum, count2. avg/max return average/max for each group

Example: Report the average, maximum amount, and number of loans by branch

branch_name Avg Max no_loans

Pennyridge 1400 1500 2

Downtown 1000 1000 1

Redwood 2000 2000 1

Mianus 500 500 1

Round Hill 900 900 1

LOAN

Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


SQL select: group by, having

select loan_number, amount, count( loan_number) as no_debtorsfrom loan, borrowswhere loan_number = loan_no and amount <= 1500group by loan_numberhaving count(loan_number) >= 2

‘having’ conditions are only applied to data after rows have been grouped‘order by’ used with ‘group by’ will be applied to groups.

‘having’ is used to screen out groups from the output

Example: Report the small loans (<= 1500) held by 2 or more people.

BORROWS

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_noLOAN

Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


loan_number amount no_debtors

L17 1000 3

SQL select: date functions

select c_ssnfrom depositwhere datediff( yy, accessDate, getdate( ) ) > 5

datediff units: yy (years), …, ns (nano-seconds)

SQL provides special functions to handle dates, times and strings

c_ssn ac_num accessDate

888-12-0000 A201 Mar 1, 98

DEPOSIT

Mar 1, 09A217111-12-0000

Feb 25, 09A101000-12-0000

888-12-0000

555-00-0000

333-12-0000

222-12-0000

888-12-0000

c_ssn

Mar 1, 98A201

Mar 10, 09A305

Feb 28, 09A102

Feb 1, 09A215

Jan 1, 09A101

accessDateac_num

Mar 1, 09A217111-12-0000

Feb 25, 09A101000-12-0000

888-12-0000

555-00-0000

333-12-0000

222-12-0000

888-12-0000

c_ssn

Mar 1, 98A201

Mar 10, 09A305

Feb 28, 09A102

Feb 1, 09A215

Jan 1, 09A101

accessDateac_num

Example: report those customers who have been inactive for over 5 years

SQL select: string functions

select ssn, name, street, cityfrom customerwhere name LIKE ‘J%’ or street LIKE ‘[^mnp]%’ or city LIKE ‘%[ ]%’

Wildcards:% zero or more chars[asd] match one char out of list [asd][^asd] matches any one char except a, s, d.

It is often useful to use wild-cards for string matching

ssn name street city

111-12-0000 Jones Main Harrison

777-12-0000 Adams Spring Pittsfield

888-12-0000 Johnson Alma Palo Alto

999-12-0000 Brooks Senator Brooklyn

CUSTOMER

DO888-99-9999StamfordPutnamTurner555-12-0000

LO333-11-4444PrincetonNassauWilliams666-12-0000

LO123-45-6789PittsfieldSpringAdams777-12-0000

DO888-99-9999Palo AltoAlmaJohnson888-12-0000

LO123-45-6789BrooklynSenatorBrooks999-12-0000

Pittsfield

Rye

Harrison

Rye

Harrison

city

Park

North

Main

North

Main

street

888-99-9999

333-11-4444

321-32-4321

321-32-4321

321-32-4321

banker

DOLindsay000-12-0000

444-12-0000

333-12-0000

222-12-0000

111-12-0000

ssn

LOCurry

CRMHayes

CRMSmith

CRMJones

b_typename






Pittsfield

Rye

Harrison

Rye

Harrison

city

Park

North

Main

North

Main

street

888-99-9999

333-11-4444

321-32-4321

321-32-4321

321-32-4321

banker


444-12-0000

333-12-0000

222-12-0000

111-12-0000

ssn

LOCurry

CRMHayes

CRMSmith

CRMJones

b_typename

SQL as a DML: update command…

update loanset amount = amount - 200where loan_number = ( select loan_no

from borrows, customerwhere customer = ssn and name = ‘Jones’ )

To modify an entry in a cell

LOAN

Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


Pennyridge1300L16

Round Hill900L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown1000L17


BORROWS

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

CUSTOMER






Pittsfield

Rye

Harrison

Rye

Harrison

city

Park

North

Main

North

Main

street

888-99-9999

333-11-4444

321-32-4321

321-32-4321

321-32-4321

banker


444-12-0000

333-12-0000

222-12-0000

111-12-0000

ssn

LOCurry

CRMHayes

CRMSmith

CRMJones

b_typename






Pittsfield

Rye

Harrison

Rye

Harrison

city

Park

North

Main

North

Main

street

888-99-9999

333-11-4444

321-32-4321

321-32-4321

321-32-4321

banker


444-12-0000

333-12-0000

222-12-0000

111-12-0000

ssn

LOCurry

CRMHayes

CRMSmith

CRMJones

b_typename

LOAN

Pennyridge1300L16

Round Hill700L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown800L17


Pennyridge1300L16

Round Hill700L11

Mianus500L93

Pennyridge1500L15

Redwood2000L23

Downtown800L17


select * from loan

SQL as a DML: delete command…

delete from loan

To delete a row from a table

BORROWS

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

L17999-12-0000

L11111-12-0000

L16777-12-0000

666-12-0000

444-00-0000

333-12-0000

222-12-0000

111-12-0000

customer

L17

L93

L15

L23

L17

loan_no

CUSTOMER






Pittsfield

Rye

Harrison

Rye

Harrison

city

Park

North

Main

North

Main

street

888-99-9999

333-11-4444

321-32-4321

321-32-4321

321-32-4321

banker


444-12-0000

333-12-0000

222-12-0000

111-12-0000

ssn

LOCurry

CRMHayes

CRMSmith

CRMJones

b_typename






Pittsfield

Rye

Harrison

Rye

Harrison

city

Park

North

Main

North

Main

street

888-99-9999

333-11-4444

321-32-4321

321-32-4321

321-32-4321

banker


444-12-0000

333-12-0000

222-12-0000

111-12-0000

ssn

LOCurry

CRMHayes

CRMSmith

CRMJones

b_typename

all rows of loan table deleted

delete from customerwhere name = ‘Jones’

request to delete row of customer tablewith name = ‘Jones’[will it succeed ?]

Views in SQL

A view is a virtual table defined on a given Database:

The columns of the view are either(i) columns from some (actual or virtual) table of the DB

or (ii) columns that are computed (from other columns)

Main uses of a view:

- Security (selective display of information to different users)

- Ease-of-use-- Explicit display of derived attributes-- Explicit display of related information from different tables-- Intermediate table can be used to simplify SQL query

Create a view showing the names of employees, their ssn, telephone number,their manager's name, and how many years they have worked in the bank.

create view bank_employee as select e.e_ssn as ssn, e.e-name as name, e.tel as phone, m.e-name as manager, datediff( yy, start_date, getdate( )) as n_years from EMPLOYEE as e, EMPLOYEE as m where e.mgr_ssn = m.e_ssn

select * from bank_employee

Views in SQL..

ssn name phone manager n_years

111-22-3333 Jones 12345 Adams 15

333-11-4444 Smith 54321 Jones 12

123-45-6789 Lee 54321 Jones 12

555-66-8888 Turner 55555 Adams 8

987-65-4321 Jones 87621 Chan 15

888-99-9999 Chan 87654 Black 30

321-32-4321 Adams 77777 Black 30

777-77-7777 Black 99111 null 30

View definition is persistent – once you define it, the definition stayspermanently in the DB until you drop the view.

Operations on Views

You can use the view in any SQL query just the same as any other table, BUT(1) You cannot modify the value of a computed attribute(2) If an update/delete command is execute, the underlying data in the referenced table of the view is updated/deleted. [this can cause unexpected changes in your DB]

The DBMS only computes the data in a view when it is referencedin a SQL command (e.g. in a select … command)no physical table is stored in the stored memory corresponding to the view.

SQL language has some other useful commands and operators [e.g. see here]

In addition, most DBMS will provide many non-standard operators and servicesto facilitate information system deployment and administration.

DBMSs can handle very large amount of data, and process queries very fast.IBM’s DB2 can handle over 6m transactions per min (tpm); Oracle 10g, over 4m tpm

To speed up queries, you can use indexes.

Common DBMSs: IBM DB2, Oracle 10g, Microsoft SQL Server, Sybase, MySQL.all support SQL.

Concluding remarks on SQL

Most people use DBs, but always through some computer program interface (API).

Most DBMSs will provide program ‘libraries’ (a collection of a set of compliedfunctions) with functions to: - Connect to the DBMS - Select a DB - Send a SQL command, and receive the response in some standard data structure.

Each DBMS provides one library for each programming language.

On Windows™ (and several other) systems, these libraries are called ODBC

Database API’s

DBMSDB

your codeodbc funcmore code

odbc (DLL)

Client App

SQL query

Response

Bank tables..

BRANCH

branch_name city assets

Downtown Brooklyn 9000000

Redwood Palo Alto 2100000

Pennyridge Horseneck 1700000

Mianus Horseneck 400000

Round Hill Horseneck 8000000

Pownal Bennington 300000

North Town Rye 3700000

Brighton Brooklyn 7100000

EMPLOYEE

e_ssn e_name tel start_date mgr_ssn

111-22-3333 Jones 12345 Nov-2005 321-32-4321

333-11-4444 Smith 54321 Mar-1998 111-22-3333

123-45-6789 Lee 54321 Mar-1998 111-22-3333

555-66-8888 Turner 55555 Aug-2002 321-32-4321

987-65-4321 Jones 87621 Mar-1995 888-99-9999

888-99-9999 Chan 87654 Feb-1980 777-77-7777

321-32-4321 Adams 77777 Feb-1990 777-77-7777

777-77-7777 Black 99111 Jan-1980 null

CUSTOMER

ssn name street city banker b_type

111-12-0000 Jones Main Harrison 321-32-4321 CRM

222-12-0000 Smith North Rye 321-32-4321 CRM

333-12-0000 Hayes Main Harrison 321-32-4321 CRM

444-12-0000 Curry North Rye 333-11-4444 LO

555-12-0000 Turner Putnam Stamford 888-99-9999 DO

666-12-0000 Williams Nassau Princeton 333-11-4444 LO

777-12-0000 Adams Spring Pittsfield 123-45-6789 LO

888-12-0000 Johnson Alma Palo Alto 888-99-9999 DO

999-12-0000 Brooks Senator Brooklyn 123-45-6789 LO

000-12-0000 Lindsay Park Pittsfield 888-99-9999 DO

DEPOSITc_ssn ac_num accessDate

888-12-0000 A101 Jan 1, 09

222-12-0000 A215 Feb 1, 09

333-12-0000 A102 Feb 28, 09

555-00-0000 A305 Mar 10, 09

888-12-0000 A201 Mar 1, 98

111-12-0000 A217 Mar 1, 09

000-12-0000 A101 Feb 25, 09

BORROWScustomer loan_no

111-12-0000 L17

222-12-0000 L23

333-12-0000 L15

444-00-0000 L93

666-12-0000 L17

111-12-0000 L11

999-12-0000 L17

777-12-0000 L16

LOANloan_number amount branch_name

L17 1000 Downtown

L23 2000 Redwood

L15 1500 Pennyridge

L93 500 Mianus

L11 900 Round Hill

L16 1300 Pennyridge

Not all tables of our normalizeddesign are shown; please createand populate for practice.

References and Further Reading

Silberschatz, Korth, Sudarshan, Database Systems Concepts, McGraw Hill

Next: IS for non-structured data

ielm 511: information system design

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