mis awe pp chapter 5

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5-0© Pearson Education 2013

Management Information SystemsArab World Edition

Laudon, Laudon, Elragal

Chapter 5:

Foundations of BusinessIntelligence: Databasesand InformationManagement

Lecturer:

Ahmed Elragal



Chapter Learning Objectives

© Pearson Education 2013

After reading this chapter, you will be able to answer the

following questions:1. What are the problems of managing data resources in a

traditional file environment and how are they solved by adatabase management system (DBMS)?

2. What are the major capabilities of a DBMS and why is a relational

DBMS so powerful?

3. What are some important principles of database design?

4. What are the principal tools and technologies for accessinginformation from databases to improve business performance anddecision making?

5. Why are information policy, data administration, and data qualityassurance essential for managing the firm’s data resources?

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Organizing Data in a Traditional FileEnvironment


File organization concepts

Database: Group of related files

File: Group of records of same type

Record: Group of related fields

Field: Group of characters as word(s) or number:

• Describes an entity (person, place, thing on which we storeinformation)

• Attribute: Each characteristic, or quality, describing entity

Example, Attributes Date or Grade belong to entity COURSE

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The data hierarchy

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FIGURE 5-1

A computer systemorganizes data in ahierarchy that starts withthe bit, which representseither a 0 or a 1. Bits canbe grouped to form a byteto represent onecharacter, number, orsymbol. Bytes can begrouped to form a field,and related fields can begrouped to form a record.Related records can be

collected to form a file,and related files can beorganized into a database.





Problems with the traditional file environment (files

maintained separately by different departments)

Data redundancy:

• Presence of duplicate data in multiple files

Data inconsistency:

• Same attribute has different values

Program-data dependence:

• When changes in program requires changes to data accessed

by programLack of flexibility

Poor security

Lack of data sharing and availability

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Traditional file processing

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FIGURE 5-2 The use of a traditional approach to file processing encourages eachfunctional area in a corporation to develop specialized applications.Each application requires a unique data file that is likely to be a subsetof the master file. These subsets of the master file lead to dataredundancy and inconsistency, processing inflexibility, and wastedstorage resources.



The Database Approach to Data Management


Database:

• Serves many applications by centralizing data and controllingredundant data

Database management system (DBMS):• Interfaces between applications and physical data files

• Separates logical and physical views of data

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Database management system (cont.):

• Solves problems of traditional file environment:

− Controls redundancy

− Eliminates inconsistency

− Uncouples programs and data

− Enables organization to centrally manage data and datasecurity

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Relational DBMS:

• Represent data as two-dimensional tables called relations orfiles

•

Each table contains data on entity and attributes

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Table (grid of columns and rows):

• Rows (tuples): Records for different entities

• Fields (columns): Represents attribute for entity

• Key field: Field used to uniquely identify each record

• Primary key: Field in table used for key fields

• Foreign key: Primary key used in second table as look-up fieldto identify records from original table

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Relational database tables

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FIGURE 5-4 A relational database organizes data in the form of two-dimensionaltables. Illustrated here is the table for the entity SUPPLIER showinghow they represent each entity and its attributes. Supplier Number is aprimary key for the SUPPLIER table which is on the next slide and aforeign key for the PART table.





Relational database tables (cont.)

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FIGURE 5-4(cont)

A relational database organizes data in the form of two-dimensionaltables. Illustrated here is the table for the entity PART showing howthey represent each entity and its attributes. Supplier Number is aprimary key for the SUPPLIER table and a foreign key for the PARTtable (which is on the previous slide).





Operations of a Relational DBMS

Three basic operations used to develop useful sets of data:

• SELECT: Creates subset of data of all records that meet stated

criteria• JOIN: Combines relational tables to provide user with more

information than available in individual tables

• PROJECT: Creates subset of columns in table, creating tableswith only the information specified

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The three basic operations of a relational DBMS

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The select, join, and project operations enable data from two differenttables to be combined and only selected attributes to be displayed.

FIGURE 5-5





Three basic operations used to develop useful sets of data

Object-Oriented DBMS (OODBMS):

• Stores data and procedures as objects

• Objects can be graphics, multimedia, Java applets

• Relatively slow compared with relational DBMS for processinglarge numbers of transactions

• Hybrid object-relational DBMS: Provide capabilities of bothOODBMS and relational DBMS

Databases in the cloud:

• Typically less functionality than on-premises DBs

• Amazon Web Services, Microsoft SQL Azure

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Capabilities of database management systems

Data definition capability: Specifies structure of database content,

used to create tables and define characteristics of fields

Data dictionary: Automated or manual file storing definitions of

data elements and their characteristicsData manipulation language: Used to add, change, delete, retrieve

data from database

• Structured Query Language (SQL)

• Microsoft Access user tools for generation SQL

Many DBMS have report generation capabilities for creating

polished reports (Crystal Reports)

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Microsoft Access data dictionary figures

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FIGURE 5-6

Microsoft Access has arudimentary datadictionary capabilitythat displaysinformation about thesize, format, and other

characteristics of eachfield in a database.Displayed here is theinformation maintainedin the SUPPLIER table.The small key icon tothe left of

Supplier_Numberindicates that it is akey field.





Example of an SQL Query

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FIGURE 5-7 Illustrated here are the SQL statements for a query to select suppliersfor parts 137 or 150. They produce a list with the same results asFigure 5-5.





An Access Query

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FIGURE 5-8

Illustrated here ishow the query inFigure 5-7 would beconstructed usingMicrosoft Accessquery building

tools. It shows thetables, fields, andselection criteriaused for the query.





• Conceptual (logical) design: Abstract model from businessperspective

• Physical design: How database is arranged on direct-accessstorage devices

Design process identifies:

• Relationships among data elements, redundant databaseelements

• Most efficient way to group data elements to meet business

requirements, needs of application programs

Normalization is streamlining complex groupings of data tominimize redundant data elements and awkward many-to-manyrelationships

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Designing databases





An unnormalized relation for order

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FIGURE 5-9 An unnormalized relation contains repeating groups. For example,there can be many parts and suppliers for each order. There is only aone-to-one correspondence between Order_Number and Order_Date.





Normalized tables created from order

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FIGURE 5-10 After normalization, the original relation ORDER has been broken downinto four smaller relations. The relation ORDER is left with only twoattributes and the relation LINE_ITEM has a combined, or concatenated,key consisting of Order_Number and Part_Number.





Entity-relationship diagram:

• Used by database designers to document the data model

• Illustrates relationships between entities

Distributing databases (storing database in more than oneplace):

• Partitioned: Separate locations store different parts ofdatabase

•

Replicated: Central database duplicated in entirety at differentlocations

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Designing databases (cont.)



Using Databases to Improve BusinessPerformance and Decision Making


Very large databases and systems require special capabilities,tools:

• To analyze large quantities of data

•

To access data from multiple systemsThree key techniques:

1. Data warehousing

2. Data mining

3. Tools for accessing internal databases through the web

5-25





Data warehouse:

• Stores current and historical data from many coreoperational transaction systems

•

Consolidates and standardizes information for use acrossenterprise, but data cannot be altered

• Data warehouse system will provide query, analysis, andreporting tools

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Components of a data warehouse

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FIGURE 5-12 The data warehouse extracts current and historical data from multipleoperational systems inside the organization. These data are combinedwith data from external sources and reorganized into a central databasedesigned for management reporting and analysis. The informationdirectory provides users with information about the data available in thewarehouse.

.





Tools for consolidating, analyzing, and providing access to vastamounts of data to help users make better business decisions

Principle tools include:

•

Software for database query and reporting• Online analytical processing (OLAP)

• Data mining

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Business intelligence





The multidimensional data model

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FIGURE 5-15

The view that isshowing is productversus region. If yourotate the cube 90degrees, the face thatwill show is productversus actual and

projected sales. If yourotate the cube 90degrees again, youwill see region versusactual and projectedsales. Other views arepossible.





More discovery driven than OLAP

Finds hidden patterns, relationships in large databases and infersrules to predict future behavior

Example, finding patterns in customer data for one-to-onemarketing campaigns or to identify profitable customers.

Types of information obtainable from data mining:

• Associations

•

Sequences• Classification

• Clustering

• Forecasting

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Data mining:





Predictive analysis:

• Uses data mining techniques, historical data, and assumptionsabout future conditions to predict outcomes of events

•

Example, Probability a customer will respond to an offerText mining:

• Extracts key elements from large unstructured data sets (e.g.,stored e-mails)

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Discovery and analysis of useful patterns and information fromweb

• Example, to understand customer behavior, evaluateeffectiveness of website, etc.

Web content mining

• Knowledge extracted from content of web pages

Web structure mining

•

Example, links to and from web pageWeb usage mining

• User interaction data recorded by web server

5-34

Web mining:





Many companies use the web to make some internal databasesavailable to customers or partners

Typical configuration includes:

• Web server

• Application server/middleware/CGI scripts

• Database server (hosting DBM)

Advantages of using the web for database access:

• Ease of use of browser software

• Web interface requires few or no changes to database

• Inexpensive to add web interface to system

5-35

Databases and the web:





Linking internal databases to the web

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FIGURE 5-16 Users access an organization’s internal database through the webusing their desktop PCs and web browser software.

.



Big Data


Big data is:

• Extreme data management

• Data sets that are large enough to go beyond the capability ofthe traditional DBMS to control and maintain

• Characterized by the 3Vs: volume, variety, and velocity,where volume is large, variety high, and rate of change rapid.

Example, the Sloan Digital Sky Survey (SDSS) begancollecting data in 2000 and during first few weeks collected

more data than the amount collected in the entire history ofastronomy.

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Managing Data Resources


Firm’s rules, procedures, roles for sharing, managing,standardizing data

Data administration:

• Firm function responsible for specific policies and proceduresto manage data

Data governance:

• Policies and processes for managing availability, usability,integrity, and security of enterprise data, especially as it

relates to government regulations

Database administration:

• Defining, organizing, implementing, maintaining database;performed by database design and management group

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Establishing an information policy:



Managing Data Resources

Data quality audit:

• Structured survey of the accuracy and level of completenessof the data in an information system

− Survey samples from data files, or

− Survey end users for perceptions of quality

Data cleansing:

• Software to detect and correct data that are incorrect,

incomplete, improperly formatted, or redundant• Enforces consistency among different sets of data from

separate information systems

Ensuring data quality:

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