Lecture 2

ISM - © 2010 Houman Younessi

Convener:

Houman Younessi

1-860-548-7880

youneh@rpi.edu

Information SystemsSpring 2011

Lecture 2

ISM - © 2010 Houman Younessi

Element Concept Information Category Information System

Revenue Demand Market trends and marketingProduct qualityPricing

Data Acquisition Data AnalysisControlForecastingOptimization

Product Orientation

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Quality

- Design - Meeting requirements

- Control - Meeting specifications

- Delivery - Meeting expectations

Example: Hospital

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The pitfall of Ceteris Paribus• The demand side of the market can be represented by the demand curve

• The shape of the demand curve determines demand points (levels of demand)

• Demand points in turn determines supply levels needed to maximize revenues

However

The demand curve (function) changes and shifts with respect to changes in consumer taste, income, population, commodity prices, availability of other

products, product quality, access, and price stability

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ISM - © 2010 Houman Younessi

Consumer taste,

Income,

Population,

Commodity prices,

Availability of other products,

Product quality,

Access, and

Price stability

We need to not only acquire data on these but also to analyze and

present the information such data might imply.

• Data Acquisition • Data Analysis• Control• Forecasting, and• Optimization

applications are to be used.

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ISM - © 2010 Houman Younessi

Application:Collection of programs that together achieve a particular objective directly related to a task that the user wishes to perform.

Program:

Code written - in a human understandable language - that is to be executed in computer memory where it can perform tasks on data.

Algorithms + Data Structures

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ISM - © 2010 Houman Younessi

Algorithm:

A finite set of well-defined instructions for accomplishing a given task which, given an initial state, will terminate in a defined end-state representing a particular goal.

e.g. A recipe to cook lasagna

e.g. A set of instructions to minimize a path traveled

e.g. A set of instructions to sort a set of numbers

Recursive, iterative; Deterministic, Non-deterministic; Serial, Parallel

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ISM - © 2010 Houman Younessi

Examples of Algorithms:

Recursive Iterative

function fib(n)

if n = 0

return 0

if n = 1

return 1

else

return fib(n-1) + fib(n-2)

function fib(n)

a, c = 0 ,b = 1

Do (n times)

{ c = a+b

a = b

b = c

return b}

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ISM - © 2010 Houman Younessi

Programming Language:Artificial Language created to produce artifacts called programs that control the behavior of automata, usually a computer.

Compilers, Interpreters;

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ISM - © 2010 Houman Younessi

Example Programs in Various Languages:

int fib(int n) {

if (n <= 2) return 1

else return fib(n-1) + fib(n-2) }

(+ (fib(- N 1)) (fib(- N 2)))))

fib1,fib2 :=1

to n do begin

fib1,fib2 :=fib2,fib1; fib1 :=fib1+fib2

end;

C family

Lisp family

Algol family

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ISM - © 2010 Houman Younessi

Data Structure:

A well-defined form of storing data.

• Influences the efficiency of algorithm used.

• Abstract (Data-type), Concrete (Implementation);

• Simple, Composite;

Implemented in Memory

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Example Data Structure: Stack

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Database:A system that provides organized collection, retention and presentation of data according to a well-defined model that ensures user selected persistence.

• Definition and query schemas,

• Models (Hierarchical, networked, relational, object)

• Transaction

• Concurrency

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Application Types:

- Compiler

- Operating System

- DBMS

- Accounting and financial management

- Inventory management

- CAD

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ISM - © 2010 Houman Younessi

Building a Database

Step 1:

Capturing the Data Model

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ISM - © 2010 Houman Younessi

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ISM - © 2010 Houman Younessi

Step 2

NORMALIZATION

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What is Normalization?

Normalization is the process of efficiently organizing data in a database. There are two goals of the normalization process: eliminating redundant data (for example, storing the same data in more than one table) and ensuring data dependencies make sense (only storing related data in a table). Both of these are worthy goals as they reduce the amount of space a database consumes and ensure that data is logically stored.

There are five normal forms (1st to 5th). These are cumulative in that to be in 2nd normal form the data has to be in 1st normal form first.

The first to third normal forms are almost always obeyed. The fourth normal form occasionally, and the fifth normal form almost never.

We will cover the first three normal forms here only.

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First Normal Form (1NF) * Eliminate duplicative columns from the same table. * Create separate tables for each group of related data and identify each row with a unique column or set of columns (the primary key).

Second Normal Form (2NF) * Meet all the requirements of the first normal form. * Remove subsets of data that apply to multiple rows of a table and place them in separate tables. * Create relationships between these new tables and their predecessors through the use of foreign keys.

Third Normal Form (3NF) * Meet all the requirements of the second normal form. * Remove columns that are not dependent upon the primary key.

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ISM - © 2010 Houman Younessi

First Normal Form:

• Eliminate duplicative columns from the same table.• Create separate tables for each group of related data and identify each row with a unique column (the primary key).

Manager Subordinate 1 Subordinate 2 Subordinate 3 Subordinate 4

We can now eliminate the repeating groups by forming a table such as

Subordinate Manager

We can now ensure that each entry is identified by a single identifier:

Subordinate ID Manager ID Subordinate Manager

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ISM - © 2010 Houman Younessi

Second Normal Form

• Remove subsets of data that apply to multiple rows of a table and place them in separate tables.• Create relationships between these new tables and their predecessors through the use of foreign keys.

reduce the amount of redundant data in a table by extracting it, placing it in new table(s) and creating relationships between those tables.

CUS_ID FIRST LAST STREET CITY STATE ZIP

CUS_ID FIRST LAST STREET ZIP

ZIP CITY STATE

to

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ISM - © 2010 Houman Younessi

Third Normal Form

Remove columns that are not fully dependent upon the primary key.

CUS_ID PROD_ID UNIT_PR QTTY TOTAL

To:

CUS_ID PROD_ID UNIT_PR QTTY

“TOTAL” is derivable as TOTAL=UNIT_PR*QTTY

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