Alter – Information Systems 4th ed. © 2002 Prentice Hall 1 Information and Databases.

1 Alter – Information Systems 4th

ed. © 2002 Prentice Hall

Information and Databases

Alter – Information Systems 4th ed. © 2002 Prentice Hall2

Opening Case: eBay

A PURE INFORMATION business It creates values purely by processing the

information required to conduct online auctions

Holds NO inventories Allows both individuals & companies to

participate in auctions How auctions operate

Powerful (but imperfect) trust mechanisms

Alter – Information Systems 4th

ed. © 2002 Prentice Hall3

Basic Ideas for Describing Data


Types of Data

Predefined data items Text Images Audio Video

The only types used by traditional business systems


Types of Data in Today’s Information systems

Pre-defined Data - numerical or text items whose meaning are specified explicitly.

Text - letters, numbers, and other characters where the meaning is not pre-defined.

Images - data in the form of pictures Audio - data in the form of sound Video - combination of pictures and sound

displayed over time. Future types: taste and smell?

6 Alter – Information Systems 4th ed. © 2002 Prentice Hall

Images produced by information systems


What Is a Database?

A structured collection of ELECTRONICALLY STORED data Controlled & accessed through computers The structure is given by predefined predefined

relationshipsrelationships between predefined types of predefined types of data items data items

May include any of the five types of data


Database management system (DBMS) = an integrated set of programs, used to define, update, and control the database


Files- Figure 4.2

A set of related records that contain the same fields in the same order and format Key = a fields that uniquely identifies each record


Logical vs. Physical Views of the Data

People need a model of how the data is stored in the database DATA MODEL = a logical description of the

structure of the data Logical view of data = how people think

about the data Physical view of the data = how the

computer “thinks” about the data


Figure 4.3


The Process of Accessing Data

Push vs. pull Push systemPush system = the information is provided to

the user automatically Pull systemPull system = the user requests the

information each time it is needed PreprogrammedPreprogrammed vs. ad hocad hoc Push systems are preprogrammed, while

pull systems are ad hoc



Data Modeling

Defining and Organizing the Data


Data Modeling: Documenting Information Architecture

Information Architecture - a conceptualization of how the information requirements are met by the system.

From the user’s viewpoint: What information is in the system? How is the information organized? How can users obtain whatever information

they need?


Entity Relationship Diagrams

What kinds of things does the system collect information about? entities

What is the relationship between these entities? Relationship or association among entities

What specific information does it collect about each of those things? attributes


Entity-relationship diagram for part of a university registration system


Types of relationships in entity-relationship


Possible Attributes for the Entity Types

DEPARTMENT•Department identifier•College•Department head•Scheduling coordinator

COURSE•Course number•Department •Required of department major (y/n)•Course description

SECTION•Section identification number•Semester•Year•Classroom•Start time•End time•Days of week for class meetings

PROFESSOR•Employee identification number•Name•Address•Birthdate•Office telephone•Social Security number

STUDENT•Student identification number•Name•Address•Birthdate•Telephone•Gender•Ethic group•Social Security number

OFFICE•Office number•Building•Telephone extension


Use of E-R Diagrams

E-R Diagrams are actually used for the non-technical purpose of identifying the types of things within the system’s scope and the relationships among these types of things.


ERDs help determine what data will be included, and how the database will be structured

Excellent communication mediumcommunication medium between users and developers



Types of Databases


Relational Databases

The predominant database technology A set of tables linked through shared

key attributes ERDs constitute a good starting point for

defining the tables and the keys in a relational database


E-R Diagram from a Relational Database – (Figure 4.6 MS-Access)


Normalization = a technique for designing a good set of tables Eliminates redundancies and inconsistent

dependencies Structured Query Language (SQL) – the

standard language for creating and manipulating relational databases


Some new Data base Concepts

Multi-dimensional databases: most relational database models are optimized to

support transaction processing. Business professionals often wish to analyze large

amounts of data frequently, e.g. along dimensions of product, time period, and store.

There is a significant difference between transaction processing vs. analytical processing.

Multi-dimensional databases help support data warehouses which we will discuss further later in the semester.


Multidimensional Databases

Relational databases are not appropriate when the data in massive databases must be analyzed

Multidimensional database – a large database used for data analysis Can be viewed as a single table, where each

column represents a different dimension


Multi-dimensional Databases Transaction Systems:

Insert an order for 300 baseballs Update this passenger’s airline reservation. close-out accounts payable records for this vendor. What is the current checking account balance for this

customer? Analytical Support Systems:

Did the sales promotion last quarter do better than the same promotion last year?

Is the five-day moving average for this security leading or trailing actual prices?

Which product line sells best in middle-America and how does this correlate to demographic data.


A Multidimensional database


Slicing and Dicing


Slicing and dicing – analyzing the data in a variety of ways to better understand it, and get answers to business questions


Data Warehouses

A system designed to support business analysis and management decision making Typically supported by multidimensional

databases An alternative to databases used to support

business transactions Data mart = a smaller data warehouse

used by a business function or department


Maintaining a Data warehouse


Geographic Information Systems

Organizing data so that it can be accessed by pointing at a region on a map.

Based on spatial or geographic coordinates. Marketing and planning applications can

visualize customers The important distinction between GIS and other

types of information systems is not in the database, but in the access method (i.e. through maps).


Geographical Information Systems (GISs)

Permit the user to access data based on spatial or geographic coordinates

Consist of: A database Software that allow data to be used by

selecting locations on a map


A geographical information system


Text & Image Databases

TEXT databases = set of electronic documents Individual documents or information within

documents can be retrieved Typically use hypertext to link the documents

IMAGE databases – store images and their descriptions Increasingly important (online catalogs)


Hypermedia Databases and the Web

Hypermedia database = a database that uses hypertext links to organize DocumentDocument files

Text Images Data Audio Video

ExecutableExecutable files


The Web Not a hypertext database since its content is

not defined and controlled Web page URL Browser HTML XML Applets


Retrieving a web page requires passing messages between different computers - Figure 4.13


Indexes & search engines Index = a list structure organized to identify

and locate documents related to a specific topic

Multilayer indexes Search engine = software that identifies Web

pages based on user supplied KEYWORDS Query tools for the Web take into account the

fact that the Web lacks predefined data definitions



Database Management Systems (DBMSs)

Control and organize data in the database

Facilitate programming based on the data in the database


Defining the Database and Access to Data

Data definition = identifying and describing all the data elements in the database Also known as a schema Most DBMSs support the definition of

subschemas = a “slice” of the database Data definition information is stored in the

data dictionary Describes the data metadata


Methods for Accessing Data

Sequential accessSequential access Records are processed in sequence Useful for many types of scheduled periodic

processing Impractical when immediate processing of

data is required


Figure 4.14

Direct accessDirect access – the location of the requested record is calculated

May result in collisions


Figure 4.15

Indexed accessIndexed access IndexIndex = a table used to locate data Possible to perform both sequential and direct

access efficiently indexed sequential access method (ISAM)


Processing Transactions

Controlling simultaneous access to data Locking – while a transaction uses the data

(locks it), all other transactions are prevented from using it


Distributed Databases

Data is distributed to different locations to match the way many organizations are dispersed

Centralized vs. distributed databases – tradeoffs

An alternative: database replication – complete or partial copies are stored at remote locations


Backup and Recovery

Backup = storing additional copies of data

Recovery = restoring the database to the state it had prior to a failure Based on the last complete backup + journal

of all transactions since the last backup


Database Administration

Planning for future usage Enforcing database standards Controlling database access Maintaining efficient database operation



Some Information Concepts

DataInformationKnowledge


Some Information ConceptsSome Information Concepts Data: Unorganized facts and figures. (raw material) Information: Data that has been processed into a

form that is meaningful to the recipient and is of real of perceived value in current or prospective actions or decisions.

Information: adds to a representation corrects or confirms previous information has “surprise” value in that it tells us something we did not

know, or could not predict. What is a “finished product” to one, may be “raw

materials” to someone else.


Definitions: Information vs. Knowledge

Knowledge: a combination of instincts, ideas, rules, and procedures that guide actions and decisions.

Helping to provide the best available knowledge to decision-making is another role of information systems


Relationship Between Data, Information, and Knowledge

The difference between data and information is easy to remember.

It is often cited as the reason why systems that collect large amounts of information fail to meet management’s information needs.

There are many methods of converting data into information for decision making.

Managers take action based on information about a current situation plus their accumulated knowledge. Actions taken feed the process of accumulating more knowledge (experience).

Example: How do medical students become competent physicians?


Relationship Between Data, Information, and Knowledge



Evaluating Data As a Resource

Information qualityInformation accessibilityInformation presentation


Attributes of Quality Information

Timeliness Completeness Conciseness Relevance Accuracy Precision Appropriateness of Form


Information Quality

Accuracy & precision Accuracy – the extent to which the information

represents what it is supposed to represent Precision – the fineness of detail

Bias and random error lead to inaccuracy

Completeness – the extent to which the available information is appropriate for the task


Age & timeliness Age – the amount of time that has passed

since the information was produced Timeliness – the extent to which the age of

the information is appropriate for the task


Source – the person or organization that produced the information Internal or external Formal or informal


Special Characteristics of Information

Usefulness - depends on combination of quality,accessibility,and presentation.

One person’s information may be another person’s noise.

Soft data may be as important as hard data. Ownership of information may be hard to

maintain. More information is not always better (information

overload). Politics can often hide or distort information.


Review: Information Needs - Operational vs.

Strategic (See Gorry and Scott-Morton Article) Time frame - historical vs. predictive for the future Currency - highly current vs. can be quite old Expectation - anticipated vs. surprise Source - largely internal vs. largely external Scope - well-defined, narrow vs. very wide Level of aggregation - detail vs. summary Frequency - real-time vs. periodic Organization - highly structured vs. loosely

structured Precision - highly precise vs. not overly precise


Question?

What special attributes or characteristics of information have affected you as an individual or as part of a group?


Information Accessibility

Availability – the extent to which the information is available in the information system

Admissibility – refers to whether laws, regulations, or culture require or prohibit the use of the information


Information Presentation

Level of summarizationLevel of summarization – a comparison between the numbers of individual items on which the data is based and the number of items in the data presented

Format Format – the way the information is organized and expressed


Information Security

ACCESS RESTRICTION – who can access what information under what circumstances

ENCRYPTION – converting data into a coded form that unauthorized people cannot decode


Determinants of Information Usefulness and Related Roles of Information Systems

INFORMATION QUALITY

•ACCURACY

•PRECISION

•COMPLETENESS

•AGE

•TIMELINESS

•SOURCE


Determinants of Information Usefulness and Related Roles of Information Systems

INFORMATION ACCESSIBILITY

•AVAILABILITY

•ADMISSIBILITY

INFORMATION PRESENTATION

•LEVEL OF SUMMARIZATION

•FORMAT

INFORMATION SECURITY

•ACCESS RESTRICTION

•ENCRYPTION


Models As Components of Information Systems

Mental models – the unwritten assumptions and beliefs used by people when thinking about a topic Often inconsistent

Mathematical models – a formal representation of the relationships between variables Compensate for the human inability to think of

too many details at the same time


What-if questions Explore the effect of alternative assumptions

about the key variables in a mathematical model

Virtual reality – a simulation of reality that permits the participant to interact with the simulated environment


Do managers expect the truth?

Alter – Information Systems 4th ed. © 2002 Prentice Hall 1 Information and Databases.

Documents

alter information systems

types of data slide

prentice hall

data push

images data

information requirements

data logical view of

data modeling