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Fundamentals of Information Systems, Seventh Edition 1 Fundamentals of Information Systems, Seventh Edition Chapter 3 Data Centers, and Business Intelligence

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Fundamentals of Information Systems, Seventh Edition

1Fundamentals of Information Systems,

Seventh Edition

Chapter 3Data Centers,

and Business Intelligence

Why Learn About Database Systems, Data

Centers, and Business Intelligence?

• Database:

– A database is an organized collection of data.

– Databases also help companies generate information to reduce costs, increase profits

• Database management system (DBMS):

– Group of programs that manipulate the database

– Provide an interface between the database and its users and other application programs

• Database administrator (DBA):

– Skilled IS professional who directs all activities related to an organization’s database

Fundamentals of Information Systems, seventh Edition

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The Hierarchy of DataBits, characters, fields, records, files,

and databases• Data is generally organized in a hierarchy that

begins with the smallest piece of data used by computers (a bit) and progresses through the hierarchy to a database.

• Bit (a binary digit):

– Circuit that is either on or off

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The Hierarchy of Data (continued)

• Byte:

– Typically made up of eight bits

– Each byte represents a character, which is the basic building block of most information.

• Character:

– Basic building block of information

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The Hierarchy of Data (continued)

• Field:

– Name, number, or combination of characters that describes an aspect of a business object or activity

• Record:

– Collection of related data fields

• File:

– Collection of related records

• Database:

– Collection of integrated and related filesFundamentals of Information Systems,

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Data Entities, Attributes, and Keys

• Entity:

• General class of people, places, or things (objects) for which data is collected, stored, and maintained.

• Examples of entities include employees, inventory, and customers.

• Attribute:

• Characteristic of an entity• For example, employee number, last name, first name, hire date, and

department number are attributes for an employee.

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• Key:

• Field or set of fields in a record that is used to identify the record

• Primary key:

• Field or set of fields that uniquely identifies the record

Data Entities, Attributes, and Keys (continued)

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The Database Approach

• The database approach:

– Traditional approach to data management:

• Each distinct operational system used data files dedicated to that system

– Database approach to data management:

• Pool of related data is shared by multiple application programs

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Traditional approach to data management

File-Based System ( traditional DB)

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The Database Approach (continued)

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Data Centers, Data Modeling and Database Characteristics

• When building a database, an organization must consider:

– Content: What data should be collected and at what cost?

– Access: What data should be provided to which users and when?

– Logical structure: How should data be arranged so that it makes sense to a given user?

– Physical organization: Where should data be physically located?

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Data Center

• Climate-controlled building or set of buildings that house database servers and the systems that deliver mission-critical information and services

• Traditional data centers:

– Consist of warehouses filled with row upon row of server racks and powerful cooling systems

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Data Center (continued)

• Many organizations now use large shipping containers packed with racks of servers and cooled to easily connect and set up

• Businesses and technology vendors working to develop green data centers that run more efficiently and require less energy for processing and cooling

• Backup and security procedures for data centers can be a concern

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Data Modeling

• Data model:

– Diagram of data entities and their relationships

• Enterprise data modeling:

– Starts by investigating the general data and information needs of the organization at the strategic level

• Entity-relationship (ER) diagrams:

– Data models that use basic graphical symbols to show the organization of and relationships between data Fundamentals of Information Systems,

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The Relational Database Model

• Relational model:

– Describes data using a standard tabular format

– Each row of a table represents a data entity (record)

– Columns of the table represent attributes (fields)

– The domain is the range of allowable values for data attributes

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The Relational Database Model (continued)

• Data cleanup

– Process of looking for and fixing inconsistencies to ensure that data is accurate and complete

– Database normalization is often used to clean up problems with data

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Normalization

• A database business process to break up data into the smallest possible parts.

• Break out all the repeating values in tables and save them into other related tables.

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Overview of Database Types

• Flat file

– Simple database program whose records have no relationship to one another

– Can called Text database

– Ex: Excel sheet

• Single user

– Only one person can use the database at a time

– Can called Desktop databse

– Examples: Access, FileMaker Pro, and InfoPath

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Database Types (Cont.)

• Multiple users ( R-DBMS)

– Allow dozens or hundreds of people to access the same database system at the same time

– Examples: Oracle, Microsoft, Sybase, and IBM

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Storing and Retrieving Data

• When an application program needs data it requests the data through the DBMS

• Concurrency control deals with the situation in which two or more users or applications need to access the same record at the same time

– It is applied to coordinate simultaneous transactions while preserving data integrity.

– It is about to control the multi-user access of database. Fundamentals of Information Systems,

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Database Management Systems

• Creating and implementing the right database system ensures that the database will support both business activities and goals

• Capabilities and types of database systems vary considerably

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Manipulating Data and Generating Reports

• Data Definition Language (DDL)

– Creating and defining database structure.

– Ex: CREATE, ALTER, DROP

• Data Manipulation Language (DML)

– Statements for managing data within database

– Ex: SELECT, INSERT, DELETE

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Manipulating Data and Generating Reports (continued)

• Structured Query Language (SQL):

– Adopted by the American National Standards Institute (ANSI) as the standard query language for relational databases

• Once a database has been set up and loaded with data, it can produce reports, documents, and other outputs

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User Views

• External schema

– To view all contents of database

• Sub-schema

– To view part of DB

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Database Administration

• DBA (Physical Design) :

– Works with users to decide the content of the database

– Works with programmers as they build applications to ensure that their programs comply with database management system standards and conventions

• Data Administrator (DA – Logical Design):

– Responsible for defining and implementing consistent principles for a variety of data issues

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Popular Database Management Systems

• Popular DBMSs for end users:

– Microsoft’s Access and FileMaker Pro

– Number of open source DBMS including PostgreSQL, MySQL, and CouchDB

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Database Virtualization

• Uses virtual servers and operating systems to allow two or more database systems, including servers and DBMSs to act like a single, unified database system

• Allows more efficient use of computing resources, reduce costs, and provide better access to critical information

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Database Virtualization (Cont.)

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Using Databases with Other Software

• DBMSs can act as front-end or back-end applications:

– Front-end applications interact directly with people

– Back-end applications interact with other programs or applications

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Linking the Company Database to the Internet

• Security always a concern when linking a database to the Internet

• Semantic Web:

– Developing a seamless integration of traditional databases with the Internet

– Provides metadata with all Web content using technology called the Resource Description Framework (RDF)

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Data Warehouses, Data Marts, and Data Mining

• Data warehouse

– Database that holds business information from many sources in the enterprise

• Data mart

– Subset of a data warehouse

• Data mining

– Information-analysis tool that involves the automated discovery of patterns and relationships in a data warehouse

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Distributed Databases

• Distributed database:

– Database in which the data may be spread across several smaller databases connected via telecommunications devices

– Gives corporations more flexibility in how databases are organized and used

• Replicated database:

– Holds a duplicate set of frequently used data.

– Can be as whole DB (Like backup) or Sub set.

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Distributed Databases (cont.)

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Figure to illustrate the idea of distributed DB

Figure to show the DB replication

Business Intelligence

• Involves gathering enough of the right information:

– In a timely manner and usable form and analyzing it to have a positive impact on business strategy, tactics, or operations

• Competitive intelligence:

– Limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations

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Business Intelligence (continued)

• Counterintelligence:

– Steps organization takes to protect information sought by “hostile” intelligence gatherers

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Summary

• Traditional file-oriented applications are often characterized by program-data dependence

• The relational model places data in two-dimensional tables

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Summary (continued)

• A DBMS is a group of programs used as an interface between a database and its users and other application programs

• DBMS basic functions include:

– Providing user views

– Creating and modifying the database

– Storing and retrieving data

– Manipulating data and generating reports

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Summary (continued)

• Database virtualization allows organizations to use computing resources more efficiently, reduce costs, and provide better data access

• Database administrator plans, designs, operates, secures, monitors, and maintains databases

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Summary (continued)

• Data warehouses are relational database management systems specifically designed to support management decision making

• Data mining allows the automated discovery of patterns and relationships in a data warehouse

• Predictive analysis combines historical data with assumptions about future conditions to forecast future events

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Summary (continued)

• Business intelligence is the process of getting enough of the right information in a timely manner and usable form

• Competitive intelligence involves information about competitors and their strategy, tactics, and operations

• Counterintelligence is the steps an organization takes to protect information from hostile intelligence gathers

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