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 11
Behind the Scenes:
Databases and Information Systems
Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall
Chapter Topics
• Database Basics
– Database Building Blocks
– Database Types
– Database Functions
• How Businesses Use Databases
– Database Warehousing and Storage
– Business Intelligence Systems
– Data Mining
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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
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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
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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
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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
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Database Building Blocks
Databases Versus Lists (cont.)
• 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
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Database Building Blocks
Databases Versus Lists (cont.)
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Database Building Blocks
Databases Versus Lists (cont.)
• 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
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Database Building Blocks
Databases Versus Lists (cont.)
• 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
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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
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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
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Database Building Blocks
Advantages of Using Databases (cont.)
• 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
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Database Building Blocks
Advantages of Using Databases (cont.)
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Database Building Blocks
Advantages of Using Databases (cont.)
• 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
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Database Building Blocks
Advantages of Using Databases (cont.)
• 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
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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
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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
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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
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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
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Database Building Blocks
Planning and Creating the Database
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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
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Database Building Blocks
Planning and Creating the Database (cont.)
• 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
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Database Building Blocks
Planning and Creating the Database (cont.)
• 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
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Database Building Blocks
Planning and Creating the Database (cont.)
• 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
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Database Building Blocks
Planning and Creating the Database (cont.)
• 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
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Database Building Blocks
Planning and Creating the Database (cont.)
• 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
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Database Building Blocks
Planning and Creating the Database (cont.)
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Database Building Blocks
Planning and Creating the Database (cont.)
• 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
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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
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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
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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
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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
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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
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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
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Database Types
Relational Databases (cont.)
• 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
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Database Types
Relational Databases (cont.)
• 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
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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
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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
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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
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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
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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
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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
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Database Functions
• Functions
– Allow users to extract subsets of data from
the database
– Output the data in a meaningful and
presentable format
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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
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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
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Database Functions
Inputting Data (cont.)
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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
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Database Functions
Data Validation
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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
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Database Functions
Data Validation (cont.)
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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
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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
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Database Functions
Viewing and Sorting Data (cont.)
• View records by
browsing
OR
• Sort records by
field name
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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
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Database Functions
Extracting or Querying Data (cont.)
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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
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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
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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
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Data Warehousing and Storage
• Simple level
– Data is retrieved as needed
– Small databases and simple enterprises
– Single database
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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
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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
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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
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Data Warehousing and Storage
Data Warehouses (cont.)
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Data Warehousing and Storage
Data Warehouses (cont.)
• 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
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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
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Data Warehousing and Storage
Populating Data Warehouses (cont.)
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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
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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
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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
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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
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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
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Business Intelligence Systems
(cont.)
• All perform similar functions
– Acquiring data
– Processing data into information
– Storing data
– Providing user with output options
– Make information meaningful and useful
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Business Intelligence Systems
(cont.)
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Business Intelligence Systems
(cont.)
• Information systems used by business
managers
– Office support systems
– Transaction-processing systems
– Management information systems
– Decision support systems
– Enterprise resource planning (ERP) systems
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Business Intelligence 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
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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
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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
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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
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Business Intelligence Systems
Transaction-Processing Systems (cont.)
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Business Intelligence Systems
Transaction-Processing Systems (cont.)
• 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
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Business Intelligence Systems
Transaction-Processing Systems (cont.)
• 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
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Business Intelligence Systems
Transaction-Processing Systems (cont.)
• 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
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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
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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
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Business Intelligence Systems
Management Information Systems (cont.)
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Business Intelligence Systems
Decision Support Systems
• Types of reports generated by MISs
– Decision support system (DSS) is another
type of business intelligence system
designed to help managers develop
solutions for specific problems
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Business Intelligence Systems
Decision Support Systems (cont.)
• Types of reports generated by MISs
(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
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Business Intelligence Systems
Decision Support Systems (cont.)
• 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
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Business Intelligence Systems
Decision Support Systems (cont.)
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Business Intelligence Systems
Decision Support Systems (cont.)
• 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
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Business Intelligence Systems
Decision Support Systems (cont.)
• 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
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Business Intelligence Systems
Decision Support Systems (cont.)
• 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 decisionmaking process of human experts
– Natural language processing (NLP) system
enables user to communicate with computer
using natural language
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Business Intelligence Systems
Decision Support Systems (cont.)
• 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
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Business Intelligence Systems
Decision Support Systems (cont.)
• 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
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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
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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
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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
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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
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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
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Data Mining (cont.)
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Chapter 11 Summary Questions
1. What is a database, and why is using one
beneficial?
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Chapter 11 Summary Questions
2. What do database management systems
do?
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Chapter 11 Summary Questions
3. What components make up a database?
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Chapter 11 Summary Questions
4. What types of databases are there?
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Chapter 11 Summary Questions
5. How do relational databases organize and
manipulate data?
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Chapter 11 Summary Questions
6. What are data warehouses and data
marts, and how are they used?
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Chapter 11 Summary Questions
7. What is a business intelligence system,
and what types of business intelligence
systems are used by decision makers?
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Chapter 11 Summary Questions
8. What is data mining, and how does it
work?
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Publishing as Prentice Hall
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