ch01 managing data

Data Management Databases and Organizations

Richard T. Watson5th Edition

Course Website (Google Group):

http://groups.google.com/group/YUC_DataManagement

Instructor:

Mousa I. Sweidan

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• TEXTBOOK:– Watson, Richard T., Data Management: Databases & Organizations,

ISBN: 0471715360, Publisher: John Wiley & Sons, Edition: 5th, 2006.

• Reference Book(s):– Hector Garcia-Molina, Jeffry D. Ullman and Jennifer D. Widom,

Database Systems the Complete Book, ISBN: 0130980439, Publisher: Prentice Hall, Year: 2002

– Ramez Elmasri, Shamkant B. Navathe, Fundamentals of Database Systems, ISBN: 0321204484. PEARSON, 4th Edition

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Course Description

• This course presents theory, concepts, and practice for database development

• Emphasis is on data modeling, database design, data integrity, SQL, and implementation of a database application

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• The course grade will be evaluated as follows:– Quizzes 10% – Labs 10%– Assignments 10%– Midterm Exam 25% – Final Exam 45%

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• Laboratory Requirement(s):

– PC with Microsoft Windows XP (or other Operating System) installed.

– Oracle 10g Express Edition (XE). • Go to www.oracle.com to download it.

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ATTENDANCE

• Excellent attendance is expected.

• If you miss class, it is your responsibility to find out about any announcements or assignments you may have missed.

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EXAMS

• The format for the exams is generally (but NOT always) as follows: Multiple-choice, Analysis, and Understanding the Course Concepts.

• The cell phones should be turned off during the examination.

• Grades will not be given out via e-mail.

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Chapter 1 :Managing Data

Fist Semester 2009/2010

• Individual data management• Organizational data management

• Components of organizational memory• Problem with data management systems • A brief history of data management system

• Data, information, and knowledge

Introduction

• Imagine what would happen to a bank that forget who owed it money or a magazine that lost the name and addresses of its subscribers.

• Organization needs data management system to record the necessary information to make a correct decision making.

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Individual Data Management

• Individual also need to manage data:• Internal memory is limited

– Limited capacity to remember many things– Overloaded with too much detail– Memory decays with time

• External memory extends internal memory– Variety of forms:

1. Calendar2. Address book3. To-do list

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1. Calendar

• Remind us of meetings and Project deadlines

• Organizing principles– Set amount of space– Ordering– Rapid access

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2. Address book

• Record the address and phone numbers of those we contact frequently.

• Organizing principles– Pre-formatted storage

space(e.g. name, city, phone, etc)

– Ordering (Alphabetic tabs)– Rapid access

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3. To do list

• Organizing principles– Structure (fairly

standard)– Rapid scan support

(Mark those tasks that have been completed)

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Comparison of data management systems

• Internal– Small– Fast– Convenient (our brain always with us)

• External– Large– Slow– Not as convenient

• The two system are interconnected, How?

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Common Features

• Features common to all data management system:– There is a storage medium– There is a structure for storing data– The storage device is organized for rapid data

entry and retrieval

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Organizational Data Management• Organizations, like people need to remember things.• A table is a common structure for storing data. (e.g. store details of

customers)• Deciding where and how to store data frequently involves a trade-off

– Access speed and cost– Storage devices are organized for rapid data entry and retrieval

• When we move from individual to organizational memory, some other factor come.– To understand these factor , we need to review the different

types of information systems

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Information Systems (IS)

• Refers to the interaction between people, processes, and technology.

• This interaction can occur within or across organizational boundaries.

• An information system is not only the technology an organization uses, but also the way in which the organization’s people interact with the technology and the way in which the technology works with the organization’s business processes.

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Types of information systems

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Type of IS System's purpose

TPS Transaction Processing System: Collects and stores data from routine transactions (e.g. purchasing, sales)

MIS Management information system: Converts data from a TPS into meaningful information for planning, controlling, and managing an organization

DSS Decision support system: Supports managerial decision making by providing models for processing and analysing data

EIS Executive information system: Provides senior management with information necessary to monitor organizational performance, and develop and implement strategies

OLAP Online analytical processing: Presents a multidimensional, logical view of data

Data mining

Uses statistical analysis and artificial intelligence techniques to identify hidden relationships in data

BI Business intelligence: Systems for gathering, storing, analyzing, and accessing data to improve decision-making

A Sample Data Cube

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Date

Produ

ct

Cou

ntr

ysum

sum TV

VCRPC

1Qtr 2Qtr 3Qtr 4Qtr

U.S.A

Canada

Mexico

sum

Business intelligence

• Refers to skills, technologies, applications and practices used to help a business acquire a better understanding of its commercial context.

• Business intelligence may also refer to the collected information itself.

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The Information Systems Cycle• Various system and technologies found in an organization are linked in a cycle.

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Store in database

Converted into information by

analysis using variety of technology

Driven by

Attributes of a Data Management System

• Desirable attributes of data required by Data Management Systems

1. Shareable2. Transportable3. Secure4. Accurate5. Timely6. Relevant

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1. Shareable

• Readily accessed by more than one person at a time.

• There are occasions when more than one person will required access to the same data at the same time.

• E.g. Two bank customer ask for information simultaneously

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2. Transportable

• Easily moved to a decision maker.

• Data should be movable from their storage locations to certain persons (such as decision makers)

• With the help of technologies.

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3. Secure

• Protected from destruction and unauthorized use.

• Different Action that organizations take to protect data against Loss, Sabotage, and Theft:– Duplicate data and store the copy or the copes, at

other locations.– Use Physical obstacle (e.g. vault) or Electronic

obstacle (e.g. password)– Non-Competition contract! (see page 13)

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4. Accurate

• Reliable, Precise records.• Organization need to remember many details

accurately– E.g. airline need accurate data to predict the

demand for each of the many flights it flies in a year.

• The quality of decision making affected with how much the data is accurate.

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5. Timely

• The value of a collection of data is often determined by its age.

• Data should be current and up-to-date

• Decision makers are most interested in current data. Why?

• Knowledge Is Power27

6. Relevant

• Relevance Is a key concern in designing a data management system

• For example Credit Card application– Relevant data might be:• Customers credit history• Employment status• Income level

– Irrelevant data:• Hair color

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Summery

• The content of data management system must be sharable, secure, and accurate

• The users of a data management system must be able to get timely and relevant data when required.

• The challenge create management system with these criteria

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Components of Organizational Memory

• An Organization’s Memory resides on a variety of media in a variety of ways

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People

• The major component of an organization memory:– Create, maintain, evolve, and use organizational memory– They know how to use all the other components

• Each person has a role and a position– How organization functions and how to process data.

• Organizational culture : is a shared beliefs, values, attributes, norm of each person in an organization

• Social networks and conversation (improve an organization products and services and learning about competitors, detect change faster and react more rapidly)

• Successful people learn how to use organizational memory, they learn what data are stored where, how to retrieve them, and how to put them together (e.g. promoting for a new product)

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Tables

• Common form of storing organization data

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Product Price

Pocket knife 4.50

Compass 10.00

Geo positioning system 500.00

Map measure 4.90

Tables cont..

• A table is a general form that describes a variety of other structures used to store data

• Example (Card file)

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Item ___________________________

Item code ________

Order point _______ Order Quantity _______

Supplier _______________________________

Supplier code _____

item Item Code Order point Order Quantity Supplier Supplier code

… … … … … …

Tables cont..

• Data stored in table typically have certain characteristics:– Data in one column are of the same type• E.g. item code -> contain number

– Data are limited by the width of available space

• Tables are a common form of storing organizational data because their structure is readily understood.

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Documents

• Example:– Reports– Manuals– Brochures– Memos

• Most document are now stored electronically such as : – Word processing files (flat, sequential text file)– Hypertext (Built-in linkages)

• Document Lack of regularity and discipline of a table.– Each row of a table has the same number of columns, but each

paragraph of a document does not have the same number of sentences.

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Multimedia• Images (identification and security, advertising and

promotional campaigns)• Graphics ( Maps, Engineering Drawings, GISs)• Audio (e.g. CD Customers usually prefer to hear a

sample of CD prior to purchase. record of the conversation between the customer and the firms representative)

• Video (e.g. auto companies now use video and virtual reality to promote their cars)

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Models

• Organization build mathematical models to describe their business. This model used during Decision support

• Used to analyze existing problems and forecast future business condition

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Knowledge

• Organization Build system to capture the knowledge of their experienced decision makers and problem solvers.

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Problems with Data Management Systems

1. Redundancy – Same data are stored in different systems

2. Lack of data control– Data are poorly managed

3. Poor interface– Data are difficult to access

4. Delays– There are frequently long delays to requests for data

5. Lack of reality– Data management system do not reflect the complexity of the real world

6. Lack of data integration– Data are dispersed across different system

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1. Redundancy

• Same data are stored in several different memories.• e.g. Customer address (which might be stored in the sales

reporting system, accounts system)

• Problems: – Change is not recorded in all systems– Duplication of effort (same item entered several times) – Storage space is wasted– Data may become inconsistent (e.g. JAN-19-1984, JAN-29-

1984)

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2. Lack of data control

• Although data are an important organizational resource, they frequently do not receive the same degree of management attention as other important organizational resources, such as people and money

• E.g. Data are stored everywhere in the organization.

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Poor interface

• User Unfriendly interface.

• User friendly interface (easy to use, intuitive)

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Delays

• Manager must make more decisions more rapidly.

• Time = Money

• Need Query Languages that provide rapid access to the data they need, in a format that they want.

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Lack of reality

• Organizational data stores must reflect the reality and complexity of the real world

• E.g. bank customer. The bank officer need full details of the customers relationship with the bank in order to make an informed decision

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Lack of data integration

• Data dispersed in different forms of organizational memory. E.g. files and image store.

• Many Data management System problem can be solved with present technology. Data Modeling and relational database technology.

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Data management systems timeline (brief history of data management system)

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Data, information & knowledge

• Data– Raw, unsummarized, and unanalyzed facts

• Information– Data processed into a meaningful form

• Knowledge– facts, truths, and beliefs, perspectives and concepts,

judgments and expectations– Support decision making. – E.g. put the right product in the right place in the

supermarket.

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Data, information & knowledgeRelationship

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DBMS functions

• The DBMS is a general-purpose software system that facilitates the processes of Defining, Constructing, Manipulating, and Sharing databases among various uses and applications.

• The main functions of DBMS:1. Defining a database: specifying the data types, structures, and

constraints of the data to be stored in the database.2. Constructing the database: the process of storing the data on some

storage medium that is controlled by the DBMS.3. Manipulating a database: includes data retrieval, data update and

reports generations.

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DBMS functions Cont..

4. Sharing a database: multiple users and programs can access the database simultaneously.

5. Protecting the database and maintaining it over a long period of time:– System protection: against hardware or software

malfunction.– Security protection: against unauthorized access.

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Database Manager, Administrator and User

• Database users may be divided into three types according to their rules and use of the database system; the following are the types of database system users:

1. Database Administrators– Authorizing access to the database.– Monitoring and coordinating the database use.– Acquiring software and hardware resources.– Controlling the database use.

2. Database Designers– Defining the content of the database.– Defining the structure of the database.– Defining the constraints of the database.– Defining functions.– Communicate with end-users for their requirements.

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Cont..3. End-users: divided into four categories:

– Casual: Access the database occasionally when needed.

– Naive or Parametric: main job function revolves around constantly querying and updating the database, using standard types of queries and updates. E.g. bank tellers check account balances.

– Sophisticated: use software packages that work with the stored database. These include business analyst, scientists, engineers who are familiar with the system capabilities.

– Stand-alone: maintain personal databases using ready-to-use packaged applications. Example, user maintains an address book.

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