technology in action - mcccokikeq/documents/chapter9.pdf · –data redundancy and inconsistency...

Technology

in Action

Alan Evans • Kendall Martin

Mary Anne Poatsy

Tenth Edition

Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall

Technology in Action

Chapter 9

Behind the Scenes:

Databases and Information Systems


Chapter Topics

• Database Basics

– Database Building Blocks

– Database Types

– Database Functions

• How Businesses Use Databases

– Database Warehousing and Storage

– Business Intelligence Systems

– Data Mining

Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall 2

Database Building Blocks

• A database is a collection of related data,

which can be

– Stored

– Sorted

– Organized

– Queried

• Databases make data more meaningful

and more useful

• Databases turn data into information

Copyright © 20134Pearson Education, Inc. Publishing as Prentice Hall 3

Database Building Blocks

• Why I need to know about databases

– Helps you interact more effectively

– Might not get the information for which you

are looking


Database Building Blocks Databases Versus Lists

• Databases are not needed for managing

all types of data

– Lists are adequate for simple tasks

– Other applications have tools to create lists

• Word

• Excel


Database Building Blocks Databases Versus Lists (cont.)

• When a list is not sufficient for organizing

data

– Lists aren’t sufficient for complex information

– Lists aren’t efficient when multiple people

need to access information



• The problem with lists

– Data redundancy occurs when there is a

Repetition of data

– Would require the updating of multiple lists

– Data inconsistency happens when not all

duplicated data is updated properly



• Other problems using lists instead of

databases

– Inappropriate data because of few checks for

invalid data

– Incomplete data due to difficulty of knowing if

or when information is missing



• When exercising caution and setting rules

are not enough

– Being careful can help, but there’s still room

for error

– Data redundancy and inconsistency are still

problems

– Complex data needs to be organized in a

database

• Most practical and efficient

• Avoids pitfalls of lists Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall 10

Database Building Blocks Advantages of Using Databases

• How databases make our lives easier

– Manage large amounts of data efficiently

– Enable information sharing

– Promote data integrity


Database Building Blocks Advantages of Using Databases (cont.)

• How databases can manage large

amounts of data efficiently

– Organize the data in specific ways

– Store in multiple lists (tables)

– Database programs are designed specifically

to manage large amounts of data accurately

as it is updated and manipulated



• How databases make information sharing

possible

– Only one file is maintained (data

centralization)

– Centralized database becomes a shared

source of information

– No files to reconcile with each other

– Controlled access increases security



• How databases promote data integrity

– Data integrity means data is accurate and

reliable

– Centralization largely ensures data integrity

– Data only needs to be updated in one place,

unlike using multiple lists



• Disadvantages associated with databases

– Can be more time consuming and expensive

to set up and administer

– Need to be careful in database design

– Database administrator is responsible for

designing, constructing, and maintaining

databases

• Needed for larger databases

– Ongoing review ensures smooth flow of data


Database Building Blocks Database Management Systems

• How databases are created

– A database management system (DBMS) is

specially designed software used to capture

and analyze data

• Oracle Database

• Microsoft Access


Database Building Blocks Database Management Systems (cont.)

• How databases are created (cont.)

– Four main operations of a DBMS

– Creating databases and entering data

– Viewing (or browsing) and sorting data

– Querying (extracting) data

– Outputting data


Database Building Blocks Database Terminology

• How data is stored in a database

– Fields

• Store each category of information

• Displayed as columns

• Identified by a field name

– Records

• Group of related fields

– Tables

• Group of related records

• Common subject


Database Building Blocks Planning and Creating the Database

• How to create a database with a DBMS

– Describe the data to be captured

• Contained in database’s files

• Referred to as the data dictionary (schema)

– Data dictionary

• Like a map of the database

• Defines the features of the fields

• Need to define for each field before data entry

• Attributes include field name, data type,

description, properties, field size


Database Building Blocks Planning and Creating the Database


Database Building Blocks Planning and Creating the Database (cont.)

• How to include data dictionary details in a

database

– Used to create the tables

– In Microsoft Access it can be created in:

• Datasheet View

• Design View: Detailed view of data elements,

known as Field Properties



• How data tables are created

– Step 1: Input unique field names

– Step 2: Define the data type

– Step 3: Set a maximum field size

– Step 4: Set a default value if necessary

• The value automatically used unless user enters

another value

• Useful for data that’s frequently the same

– Repeat for each field in the table



• How to know what fields are needed in my

database

– Careful planning is required

– Each field should describe a unique piece of

data

• Do not combine two pieces of data

• Allows for better filtering and sorting



• Adding or deleting fields from the

database

– Good planning will prevent the need to

change the structure

– Once relationships are established and data

is entered it is difficult to add or delete fields

– Enter sample or limited amounts of data to

test the database before fully populating it



• Rules for establishing field names

– Field names must be unique within a table

– Distinguish similarly named fields to avoid

confusion

– Creating a data dictionary will help you plan



• Determining what type of data can be

entered in a field

– Data type indicates what type of data can be

stored in the fields

– Prevents wrong type of data from being

entered



• Amount of data which can be entered into

a field

– Field size determines the maximum number

of characters

– Tailor the field size to match the maximum

length of the data

– If you define a field size of 50, space is

reserved for 50 characters

– Having inefficiently sized fields decreases

performance


Database Building Blocks Using Primary Keys

• Having the same values in the same table

– It is possible for fields to have the same

values

– Each record must have a unique value, the

primary key

– Primary keys make it impossible to duplicate

records


Database Building Blocks Using Primary Keys (cont.)

• A good primary key

– Must be unique

– Should not violate privacy concerns

– Doesn’t have to represent something

– AutoNumber data type (Microsoft Access) is

often used


Database Building Blocks Using Primary Keys (cont.)

• Ensuring that data is organized efficiently

– Normalization: Process of ensuring that data

is organized efficiently

• Reduces data redundancy

• Separates data into distinct tables


Database Types

• Three major types of databases are in use

– Relational

– Object-oriented

– Multidimensional

• Relational databases have the largest

market share

• Multidimensional databases are growing


Database Types Relational Databases

• Relational database

– Organizes data in table format

– Logically groups similar data into a relation

(a table that contains related data)

– Links data between tables through

relationships on common keys


Database Types Relational Databases (cont.)

• Relational database (cont.)

– The common field in one table (primary key)

is linked to the common field (foreign key) in

the second table

– Need to keep data in related tables

synchronized



• Relational database (cont.)

– Referential integrity: Each value in the

foreign table has a corresponding value in

the primary table

– Enforcing referential integrity prevents

orphan records



• Different types of relationships in relational

databases

– One-to-many: A record appears once in one

table and many times in a related table

– One-to-one: For each record in one table

there is only one record in a related table

– Many-to-many: Records in one table can be

related to multiple records in a related table

and vice versa


Database Types Object-Oriented Databases

• Object-oriented database

– Store data in objects rather than tables

– Also contain methods for processing or

manipulating data

– Can store more types of data than relational

databases

– Can access data faster


Database Types Object-Oriented Databases (cont.)

• Object-oriented database (cont.)

– Unstructured data include audio clips, video

clips, pictures, and extremely large

documents

• Binary large object (BLOB) is unstructured data

encoded in binary form

– Structured data is analytical data


Database Types Object-Oriented Databases (cont.)

• Object-oriented database (cont.)

– Based on complex models for manipulating

data

– Becoming more popular because of variety

of data

– Initially costly to convert data to object

oriented but can provide many advantages


Database Types Multidimensional Databases

• Multidimensional database

– Stored data can be analyzed from different

perspectives (dimensions)

– Relational database has only two dimensions

(fields and records)

– Multidimensional databases organize in cube

format


Database Types Multidimensional Databases (cont.)

• Multidimensional database (cont.)

– Data cube

• Measure attribute: Main type of data that cube is

tracking

• Feature attributes: Describe measure attribute in

meaningful ways


Database Types Multidimensional Databases (cont.)

• Advantages of multidimensional

databases

– Customized to provide information to variety

of users

– Process data faster

• Critical for larger databases

• Especially when accessed via the Internet


Database Functions

• Functions

– Allow users to extract subsets of data from

the database

– Output the data in a meaningful and

presentable format


Database Functions Inputting Data

• How to get data into the database

– Can be directly keyed into the database

– Can import from other files

• Saves time

• Reduces data error

• Must match the format of the database exactly

• Filters are often applied

• Nonconforming data is flagged


Database Functions Inputting Data (cont.)

• How to make manual entry into a

database more efficient

– Input forms can be used to control data input

in a shared database

– Each field has a label

– Data is inputted into the blank boxes

– Existing data can be changed through forms

– Ensures that correct record is changed


Database Functions Inputting Data (cont.)


Database Functions Data Validation

• How to ensure that only valid data is

entered into a field

– Validation is the process of ensuring that

data meets specified guidelines

– Validation rule is defined in data dictionary

– Specified in field properties for each field

– Violations result in error message with

suggested action


Database Functions Data Validation


Database Functions Data Validation (cont.)

• How to ensure that only valid data is

entered into a field (cont.)

– Common validation rules

• Range check: Data falls within range of values

– Field constraint – a property that must be satisfied

• Completeness check: Ensures all required fields

have been completed

• Consistency check: Compares values to see if

values are reasonable

• Alphabetic and numeric checks: Confirm that only

text or numbers are entered in fields


Database Functions Data Validation (cont.)


Database Functions Viewing and Sorting Data

• Viewing the data in a database

– Displaying all data at one time is an option

– Many times data is viewed one record at a

time

– Forms display individual records

• From only one table

• From related tables


Database Functions Viewing and Sorting Data (cont.)

• Reordering records in a database

– Easy to sort data in ascending or descending

order

• Step 1 - highlight a column

• Step 2 - click Ascending or Descending on the

Ribbon


Database Functions Viewing and Sorting Data (cont.)

• View records by browsing

OR

• Sort records by field name


Database Functions Extracting or Querying Data

• Learning a query language to develop

queries

– Use a filter

• Temporarily displays records that match criteria

• Can’t save the results

• Can only be applied to fields in one table

– Create a query

• Way of retrieving a particular subset of data

• Can be used from one or more tables


Database Functions Extracting or Querying Data (cont.)


Database Functions Extracting or Querying Data (cont.)

• Displaying a subset of data in a database

– Query language: Has own vocabulary and

sentence structure

– Similar to full-blown programming languages

but much easier to learn

– Structured Query Language (SQL) is the

most popular

– Modern systems provide wizards for creating

queries


Database Functions Outputting Data

• Retrieving data from of a database

– Most common output is viewable or printable

report

– Can generate reports from data in tables or

from queries

– Adjustments can be made to the report such

as grouping and compiling summary reports


Database Functions Outputting Data (cont.)

• Transferring data from a database to

another software application

– Exporting: Putting data into a format that

another application can understand

– Data can be imported and exported as well

as converted to and from other formats


Data Warehousing and Storage

• Simple level

– Data is retrieved as needed

– Small databases and simple enterprises

– Single database


Data Warehousing and Storage

(cont.)

• Problems arise when

– Organization gets much larger

– Data is stored in separate databases

• Benefits of accessing data from all

databases are being recognized


Data Warehousing and Storage Data Warehouses

• Data warehouses

– Large-scale collection of data

– Contains and organizes data in one place

– Data comes from multiple databases

– Consolidate information from various

systems to present enterprise-wide view of

operations


Data Warehousing and Storage Data Warehouses (cont.)

• Data in a data warehouse is organized the

same way as in a normal database

– Data is organized by subject

– Focus is on one specific aspect of an

operation

– Can contain information from multiple

databases



• Data warehouses do not capture data from

only one time period

– Date is time-variant; it doesn’t all pertain to

one time period

– Contains current and historical data

– Enables analysis of the past

– Examine the present in light of historical data

– Make projections about the future


Data Warehousing and Storage Populating Data Warehouses

• How data warehouses are populated with

data

– Internal sources: Company’s databases and

other analysis tools

– External sources: Data provided by vendors,

suppliers, etc.

– Clickstream data: Software which is used to

capture information about each click a user

makes


Data Warehousing and Storage Populating Data Warehouses (cont.)


Data Warehousing and Storage Data Staging

• Fitting source data into the warehouse

– Data must be “staged” before being entered

into a data warehouse

• Extraction of the data from source databases

• Transformation (reformatting) of the data

• Storage of the data in the data warehouse


Data Warehousing and Storage Data Staging

• Fitting source data into the warehouse

(cont.)

– Many programs and procedures might be

needed to extract and reformat data

– Nature and complexity of source data

determines complexity of data-staging

process


Data Warehousing and Storage Data Staging (cont.)

• How data stored in the data warehouse

can be extracted and used

– Query much same as an Access database

– Special software needed because of more

data

– Online analytical processing (OLAP)

software provides standardized tools for

viewing and manipulating data

– Enable flexible views of the data that user

can easily change


Data Warehousing and Storage Data Marts

• How to handle smaller amounts of data

– Data mart: Small slices of the data

warehouse

– Analyze a related group of data separated

from the main body of data

– Pertains to single component of business

– Vital because different data can be extracted

and reformatted

– Can be stored in specialized data marts Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall 71

Business Intelligence Systems

• Information system is software-based

solution used to gather and analyze

information

• Delivers up-to-the-minute data

• Databases, data warehouses, and data

marts are integral because they store the

functional information



(cont.)

• All perform similar functions

– Acquiring data

– Processing data into information

– Storing data

– Providing user with output options

– Make information meaningful and useful



(cont.)



(cont.)

• Information systems used by business

managers

– Office support systems

– Transaction-processing systems

– Management information systems

– Decision support systems

– Enterprise resource planning (ERP) systems



(cont.)

• Information systems used by business

managers? (cont.)

– Each system involves use of one or more

databases

– Business intelligence systems are used to

analyze and interpret data so that informed

decisions can be made

– Enable access to information from multiple

sources

– Provides information in timely fashion


Business Intelligence Systems Office Support Systems

• What an office support system

accomplishes

– Office support system (OSS) is designed to

improve communications and assist

employees in accomplishing tasks

– Example: Microsoft Office

• Maintaining phone list in Excel

• Designing sales presentation in PowerPoint

• Writing customer letters in Word


Business Intelligence Systems Transaction-Processing Systems

• Transaction-processing system

– Transaction-processing system (TPS) keeps

track of everyday business activities

– Example: Colleges

• Track frequent transactions such as registering

students, accepting payments, printing course

catalogs

– Early computers in business world hosted

TPSs


Business Intelligence Systems Transaction-Processing Systems (cont.)

• How transactions are entered into a TPS

– Entered manually or electronically

– Processed in batches or real time

– Various departments can access the TPSs to

extract necessary information



• Batch processing

– Transaction data is accumulated until point is

reached then several transactions are

processed at once

– Appropriate for activities that are not time

sensitive

– Often more efficient



• When TPS are transactions processed

– Most transactions are processed in real-time

– Real-time processing is when the database

is updated while the transaction is taking

place



• When TPS are transactions processed

(cont.)

– Example: Classes

• When registering for class the database

immediately records your registration

• Ensures you have a spot

– Online transaction processing (OLTP)

ensures that data in the TPS is current


Business Intelligence Systems Management Information Systems

• Management information system

– Management information system (MIS)

provides timely and accurate information

– Enables managers to make critical decisions

– Direct outgrowth of TPSs

– Data could be powerful if organized and

outputted in useful form

– Today’s MISs are often included as a feature

of TPSs Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall 84

Business Intelligence Systems Management Information Systems (cont.)

• Types of reports generated by MISs

– Detail report: Provides a list of transactions

that occurred during a time period

– Summary report: Provides a consolidated

picture of detailed data

– Exception report: Shows conditions that are

unusual or need attention


Business Intelligence Systems Management Information Systems (cont.)


Business Intelligence Systems Decision Support Systems


– Decision support system (DSS) is another

type of business intelligence system

designed to help managers develop

solutions for specific problems


Business Intelligence Systems Decision Support Systems (cont.)


(cont.)

– Example: Marketing Department

• Provide statistical information on customer

attributes

• Assist managers in making advertising decisions

• Uses data and enables users to add insight and

experiences and apply them to the solution



• What a DSS looks like

– DBMSs are supplemented by additional

software in a DSS

– User interface provides the means of

interaction between user and system

– Effective user interface must be easy to learn

– Other components are internal and external

data sources, model management systems,

and knowledge-based systems



• How DSSs get data

– Internal and external sources provide a

stream of data that is integrated into the DSS

• Internal sources are maintained by the company

• External sources are from any source not owned

by the company that owns the DSS



• What function a model management

system performs

– Model management system software assists

in building management models in DSSs

– Analysis tool provides view of a particular

business situation using internal and external

data

– Aids in decision making

– Used to analyze data to create additional

models



• What a knowledge-based system is, and

how it is used in DSSs

– Knowledge-based system provides

intelligence that supplements users’ intellect

and makes DSS more effective

– Expert systems try to replicate decision-

making process of human experts

– Natural language processing (NLP) system

enables user to communicate with computer

using natural language



• What a knowledge-based system is, and

how is it used in DSSs (cont.)

– Example: Apple’s Siri

– All NLP systems fall under artificial

intelligence

• Branch of computer science that attempts to

create computers that think like humans

• No computers can replicate thinking patterns of

human brain

• Scientists do not fully understand how humans

store and integrate knowledge to form intelligence



• How a knowledge-based system helps in

the decision-making process

– Fuzzy logic enables the interjection of

experiential learning into the equation by

considering probabilities

• Enables a system to be more flexible

• Consider a wider range of possibilities


Business Intelligence Systems Enterprise Resource Planning Systems

• What an enterprise resource planning

system does

– Enterprise resource planning system (ERP)

accumulates all information relevant to

running a business

– Makes information available to whoever

needs it

– Uses a common database that enables use

across multiple areas of an enterprise


Data Mining

• Data mining

– Process by which great amounts of data are

analyzed and investigated

– Objective is to spot significant patterns and

trends that would not be obvious

– Example: Enrollment data – School might

discover a consistent increase in new

engineering students who are women


Data Mining (cont.)

• Why businesses mine their data

– Understand customers better

– Effective marketing by concentrating efforts

– Data is classified, then cluster analysis

allows managers to determine trends

– Example: Potato chips and soft drinks in

same aisle


Data Mining (cont.)

• How businesses mine their data

– Classification

• Define helpful data classes

• Apply classes to unclassified data

– Estimation

• Enables managers to assign a value based on

criterion

– Affinity grouping (association rules)

• Managers determine which data goes together


Data Mining (cont.)

• How businesses mine their data? (cont.)

– Clustering

• Organizing data into similar subgroups

• No predefined classes

– Description and visualization

• Describe data so managers can interpret it in new

and different ways


Data Mining (cont.)



2. What do database management systems

do?



3. What components make up a database?



4. What types of databases are there?



5. How do relational databases organize and

manipulate data?



6. What are data warehouses and data

marts, and how are they used?



7. What is a business intelligence system,

and what types of business intelligence

systems are used by decision makers?



8. What is data mining, and how does it

work?


All rights reserved. No part of this publication may be reproduced, stored in a

retrieval system, or transmitted, in any form or by any means, electronic,

mechanical, photocopying, recording, or otherwise, without the prior written

permission of the publisher. Printed in the United States of America.


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