Transcript Slide 1

Business Driven Information Systems 2e
CHAPTER 6
DATABASES AND DATA
WAREHOUSES
McGraw-Hill/Irwin
©2009 The McGraw-Hill Companies, All Rights Reserved
SECTION 6.1
DATABASE
FUNDAMENTALS
McGraw-Hill/Irwin
©2009 The McGraw-Hill Companies, All Rights Reserved
6-3
Organizational Information
• Information is everywhere in an organization
– Data are raw facts that describe the characteristics of an event
• Sales event – date, item number, item description, quantity
ordered, customer name, shipping details
– Information is data converted into a meaningful and useful
context
• Sales event – best/worst selling item, best/worst customer
• Employees must be able to obtain and analyze the many
different levels, formats, and granularities of organizational
information to make decisions
• Successfully collecting, compiling, sorting, and analyzing
information can provide tremendous insight into how an
organization is performing
6-4
Organizational Information
• GREAT BUSINESS DECISIONS – Julius Reuter Uses
Carrier Pigeons to Transfer Information
• In 1850, the idea that sending and receiving information
could add business value was born. Julius Reuter
began a business that bridged the gap between Belgium
and Germany. Reuter built one of the first information
management companies built on the premise that
customers would be prepared to pay for information that
was timely and accurate.
• Reuter used carrier pigeons to forward stock market and
commodity prices from Brussels to Germany.
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Organizational Information
• Customers quickly realized that with the early receipt of
vital information they could make fortunes.
– Those who had money at stake in the stock market were
prepared to pay handsomely for early information from a
reputable source, even if it was a pigeon.
– Eventually, Reuter’s business grew from 45 pigeons to over 200
pigeons.
• Eventually the telegraph bridged the gap between
Brussels to Germany, and Reuter’s brilliantly conceived
temporary monopoly was closed.
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Organizational Information
• Levels, formats, and granularities
6-7
The Value of Transactional and
Analytical Information
Information Types
Range
Examples
Information Levels
Individual
Individual knowledge, goals and strategies
Department
Departmental goals, revenues, expenses, processes and
strategies
Enterprise
Enterprise-wide revenues, expenses, processes and
strategies
Document
Letters, memos, faxes, e-mails, reports, marketing
materials
Presentation
Product, strategy, process, financial, customer and
competitor presentations
Spreadsheet
Sales, marketing, industry, financial, competitor, customer,
and order spreadsheets
Database
Customer, employee, sales, order, supplier and
manufacturer
Detail (Fine)
Reports for each salesperson, product and part
Summary
Reports for all sales personnel, all products and all parts
Aggregate (Coarse)
Reports across departments, organizations and companies
Information Formats
Information Granularities
6-8
The Value of Transactional and
Analytical Information
6-9
The Value of Timely Information
• Transactional information – encompasses all
of the information contained within a single
business process or unit of work, and its primary
purpose is to support the performing of daily
operational tasks
• Analytical information – encompasses all
organizational information, and its primary
purpose is to support the performing of
managerial analysis tasks
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The Value of Timely Information
• Organizations capture and store transactional
information in databases and use it when
performing operational tasks and repetitive
decisions such as analyzing daily sales reports
and production schedules
• Transactional information examples include
withdrawing cash from an ATM, making an
airline reservation, purchasing stocks
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The Value of Timely Information
• Analytical information includes transactional
information
– Includes external organizational information such as
market, industry, and economic conditions
– Used to make ad-hoc decisions
– Includes trends, sales, product statistics, and future
growth projections
• Could also include cost/benefit analysis, sales
forecast, market trends, industry trends, and
regulations
6-12
The Value of Timely Information
• Timeliness is an aspect of information that
depends on the situation
– Real-time information – immediate, up-todate information
– Real-time system – provides real-time
information in response to query requests
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The Value of Quality Information
• Business decisions are only as good as
the quality of the information used to
make the decisions
• You never want to find yourself using
technology to help you make a bad
decision faster
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The Value of Quality Information
• Business decisions are only as good as the quality of the
information used to make the decisions
• Characteristics of high quality information include:
– Accuracy Are all the values correct? Is the name spelled correctly?
Is the dollar amount recorded properly?
– Completeness Are any of the values missing? Is the address
complete including street, city, state, and zip code?
– Consistency Is aggregate or summary information in agreement
with detailed information?
• Do all total fields equal the true total of the individual fields?
– Uniqueness Is each transaction, entity, and event represented only
once in the information?
• Are there any duplicate customers?
– Timeliness Is the information current with respect to the business
requirements? Is information updated weekly, daily, or hourly?
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The Value of Quality Information
• Low quality information example
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The Value of Quality Information
•
•
•
•
•
•
Issue 1: Without a first name it would be impossible to correlate this customer
with customers in other databases (Sales, Marketing, Billing, Customer Service)
to gain a compete customer view (CRM)
Issue 2: Without a complete street address there is no possible way to
communicate with this customer via mail or deliveries. An order might be sitting
in a warehouse waiting for the complete address before shipping. The company
has spent time and money processing an order that might never be completed
Issue 3: If this is the same customer, the company will waste money sending
out two sets of promotions and advertisements to the same customers. It might
also send two identical orders and have to incur the expense of one order being
returned
Issue 4: This is a good example of where cleaning data is difficult because this
may or may not be an error. There are many times when a phone and a fax
have the same number. Since the phone number is also in the e-mail address
field, chances are that the number is inaccurate
Issue 5: The business would have no way of communicating with this customer
via e-mail
Issue 6: The company could determine the area code based on the customer’s
address. This takes time, which costs the company money. This is a good
reason to ensure that information is entered correctly the first time. All incorrect
information needs to be fixed, which costs time and money
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Understanding the Costs of
Poor Information
•
The four primary sources of low quality
information include:
1. Customers intentionally enter inaccurate
information to protect their privacy
2. Information from different systems have
different entry standards and formats
3. Call center operators enter abbreviated or
erroneous information by accident or to save
time
4. Third party and external information contains
inconsistencies, inaccuracies, and errors
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Understanding the Costs of
Poor Information
• Potential business effects resulting from
low quality information include:
– Inability to accurately track customers
– Difficulty identifying valuable customers
– Inability to identify selling opportunities
– Marketing to nonexistent customers
– Difficulty tracking revenue due to inaccurate
invoices
– Inability to build strong customer relationships
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Understanding the Costs of
Poor Information
• Poor information could cause the SCM
system to order too much inventory from a
supplier based on inaccurate orders
• Poor information could cause a CRM
system to send an expensive promotional
item (such as a fruit basket) to the wrong
address of one of its best customers
• What occurs when you have the inability to
build strong customer relationships?
– Decreased seller power
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Understanding the Benefits of
Good Information
• High quality information can significantly
improve the chances of making a good
decision
• Good decisions can directly impact an
organization's bottom line
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Relational Database Fundamentals
• Information is everywhere in an
organization
• Information is stored in databases
– Database – maintains information about
various types of objects (inventory), events
(transactions), people (employees), and
places (warehouses)
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Relational Database Fundamentals
• Database models include:
– Hierarchical database model – information
is organized into a tree-like structure (using
parent/child relationships) in such a way that
it cannot have too many relationships
– Network database model – a flexible way of
representing objects and their relationships
– Relational database model – stores
information in the form of logically related
two-dimensional tables
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DATABASE ADVANTAGES
• Database advantages from a business
perspective include
–
–
–
–
–
–
Increased flexibility
Increased scalability and performance
Reduced information redundancy
Increased information integrity (quality)
Increased information security
Spreadsheet limitations
• Limited number of rows and columns (Excel - 65,536 rows by
256 columns) Once you use more than 65,536 rows you
have outgrown your spreadsheet
• Only one users can access the spreadsheet
• Users can view all information in the spreadsheet
• Users can change all information in the spreadsheet
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RELATIONAL DATABASE
FUNDAMENTALS
• Entity – a person, place, thing, transaction, or
event about which information is stored
– The rows in each table contain the entities
– In Figure 6.5 CUSTOMER includes Dave’s Sub Shop
and Pizza Palace entities
• Entity class (table) – a collection of similar
entities
– In Figure 6.5 CUSTOMER, ORDER, ORDER LINE,
DISTRIBUTOR, and PRODUCT entity classes
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RELATIONAL DATABASE
FUNDAMENTALS
• Attributes (fields, columns) – characteristics or
properties of an entity class
– The columns in each table contain the attributes
– In Figure 6.5 attributes for CUSTOMER include:
•
•
•
•
Customer ID
Customer Name
Contact Name
Phone
– Possible other attributes:
•
•
•
•
Address
Fax
E-mail
Cell phone
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Keys and Relationships
• Primary keys and foreign keys identify the
various entities (tables) in the database
– Primary key – a field (or group of fields) that
uniquely identifies a given entity in a table
– Foreign key – a primary key of one table that
appears an attribute in another table and acts
to provide a logical relationship among the
two tables
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Keys and Relationships
– Example
• Hawkins Shipping in the DISTRIBUTOR table
has a primary key called Distributor ID –
DEN8001
• Hawkins Shipping (Distributor ID DEN8001) is
responsible for delivering orders 34561 and
345652
• Therefore, Distributor ID in the ORDER table
creates a logical relationship (who shipped what
order) between ORDER and DISTRIBUTOR
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RELATIONAL DATABASE
FUNDAMENTALS
• How many orders have been placed for T’s Fun Zone?
– Ans: 1 Order IT 34563
• How many orders have been placed for Pizza Palace?
– Ans: None
• How many items are included in Dave’s Sub Shop’s two
orders?
– Ans: Order 34561 has 3 items and order 34562 has one item
for a total of 4 items in both orders.
• Who is responsible for distributing Dave’s Sub Shop’s
orders?
– Ans: Hawkins Shipping
• Which products are included in Order 34562?
– Ans: 300 Vanilla Coke
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• Potential
relational
database
for CocaCola
6-30
***Relational Database Advantages
• Database advantages from a business
perspective include
– Increased flexibility
– Increased scalability and performance
– Reduced information redundancy
– Increased information integrity (quality)
– Increased information security
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Increased Flexibility
• A well-designed database should:
– Handle changes quickly and easily
– Provide users with different views
– Have only one physical view
• Physical view – deals with the physical storage of
information on a storage device
– Have multiple logical views
• Logical view – focuses on how users logically
access information
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Increased Scalability and
Performance
• A database must scale to meet increased
demand/growth, while maintaining
acceptable performance levels
– Scalability – refers to how well a system can
adapt to increased demands
– Performance – measures how quickly a
system performs a certain process or
transaction
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Reduced Information Redundancy
• Databases reduce information
redundancy
– Redundancy – the duplication of information
or storing the same information in multiple
places
• Inconsistency is one of the primary
problems with redundant information
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Increase Information Integrity
(Quality)
• Information integrity – measures the quality of
information
• Integrity constraint – rules that help ensure the
quality of information
– Relational integrity constraint
• rule that enforces basic and fundamental informationbased constraints
– Business-critical integrity constraint
•
rule that enforce business rules vital to an
organization’s success and often require more insight
and knowledge than relational integrity constraints
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Increase Information Integrity
(Quality)
• Relational integrity constraint for an ordering
system
– Users cannot create an order for a nonexistent
customer
• Business-critical integrity constraints for an
ordering system
– Product returns are not accepted for fresh
product 15 days after purchase
– A discount maximum of 20 percent
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Increased Information Security
• Information is an organizational asset and
must be protected
– Access levels will typically mimic the hierarchical
structure of the organization and protect
organizational information from being viewed
and manipulated by individuals who should not
have access to the sensitive or confidential
information
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Increased Information Security
• Databases offer several security features
including:
– Password – provides authentication of the user
– Access level – determines who has access to
the different types of information
– Access control – determines types of user
access, such as read-only access
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Database Management Systems
• Database management systems (DBMS) –
software through which users and application
programs interact with a database
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Database Management Systems
• Direct interaction –
– The user interacts directly with the DBMS
– The DBMS obtains the information from the
database
• Indirect interaction
– User interacts with an application (i.e., payroll
application, manufacturing application, sales
application)
– The application interacts with the DBMS
– The DBMS obtains the information from the
database
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Data-Driven Websites
• A data-driven website is an interactive
website kept constantly updated and
relevant to the needs of its customers
through the use of a database.
– Data-driven websites are especially
useful when the site offers a great deal
of information, products, or services.
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Data-Driven Websites
– A data-driven website invites visitors to select
and view what they are interested in by
inserting a query, which the website then
analyzes and custom builds a Web page in
real-time that satisfies the query.
– The figure displays a Wikipedia user querying
business intelligence and the database
sending back the appropriate Web page that
satisfies the user’s request
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Data-Driven Websites
6-43
Data-Driven Website Business
Advantages
•
•
•
•
•
•
•
Development
Content Management
Future Expandability
Minimizing Human Error
Cutting Production and Update Costs
More Efficient
Improved Stability
6-44
Data-Driven Website Business
Advantages
• Development: Allows the website owner to make
changes any time—all without having to rely on a
developer or knowing HTML programming. A wellstructured, data-driven website enables updating with
little or no training.
• Content management: A static website requires a
programmer to make updates. This adds an
unnecessary layer between the business and its Web
content, which can lead to misunderstandings and slow
turnarounds for desired changes.
6-45
Data-Driven Website Business
Advantages
• Future expandability: Having a datadriven website enables the site to grow
faster than would be possible with a static
site. Changing the layout, displays, and
functionality of the site (adding more
features and sections) is easier with a
data-driven solution.
6-46
Data-Driven Website Business
Advantages
• Minimizing human error: Even the most competent
programmer charged with the task of maintaining many
pages will overlook things and make mistakes. This will
lead to bugs and inconsistencies that can be time
consuming and expensive to track down and fix.
Unfortunately, users who come across these bugs will
likely become irritated and may leave the site.
• A well-designed, data-driven website will have ”error
trapping” mechanisms to ensure that required
information is filled out correctly and that content is
entered and displayed in its correct format.
6-47
Data-Driven Website Business
Advantages
• Cutting production and update costs: A data-driven
website can be updated and ”published” by any
competent data entry or administrative person.
• In addition to being convenient and more affordable,
changes and updates will take a fraction of the time that
they would with a static site. While training a competent
programmer can take months or even years, training a
data entry person can be done in 30 to 60 minutes.
6-48
Data-Driven Website Business
Advantages
• More efficient: By their very nature, computers are
excellent at keeping volumes of information intact. With
a data-driven solution, the system keeps track of the
templates, so users do not have to. Global changes to
layout, navigation, or site structure would need to be
programmed only once, in one place, and the site itself
will take care of propagating those changes to the
appropriate pages and areas.
• A data-driven infrastructure will improve the reliability
and stability of a website, while greatly reducing the
chance of ”breaking” some part of the site when adding
new areas.
6-49
Data-Driven Website Business
Advantages
• Improved Stability: Any programmer who has to
update a website from ”static” templates must be very
organized to keep track of all the source files. If a
programmer leaves unexpectedly, it could involve recreating existing work if those source files cannot be
found. Plus, if there were any changes to the templates,
the new programmer must be careful to use only the
latest version. With a data-driven website, there is
peace of mind, knowing the content is never lost—even
if your programmer is.
6-50
Data-Driven Business Intelligence
6-51
Data-Driven Business Intelligence
• The customer enters search criteria in the website
• The database runs a query on the search criteria
• The company can gain BI by viewing how often items are
searched, which item is searched the most – the least,
etc.
• Companies can gain business intelligence by viewing the
data accessed and analyzed from their website.
• The figure displays how running queries or using
analytical tools, such as a Pivot Table, on the database
that is attached to the website can offer insight into the
business, such as items browsed, frequent requests,
items bought together, etc.
6-52
Integrating Information
among Multiple Databases
• Integration – allows separate systems to
communicate directly with each other
– Forward integration – takes information
entered into a given system and sends it
automatically to all downstream systems and
processes
– Backward integration – takes information
entered into a given system and sends it
automatically to all upstream systems and
processes
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Integrating Information
among Multiple Databases
• Forward integration
6-54
Integrating Information
among Multiple Databases
• Backward integration
6-55
Integrating Information
among Multiple Databases
• Building a central repository specifically
for integrated information
6-56
OPENING CASE STUDY QUESTIONS
It Takes A Village to Write an Encyclopedia
• Is an entry in Wikipedia is an example of
transactional information or analytical
information.
– From the customer’s perspective Wikipedia entries
are an example of analytical information. They are
using the information to research a topic, make a
decision, or perform an analysis. From Wikipedia’s
perspective each entry is an example of transactional
information since it is their primary business to gain
entries from individual contributors.
6-57
OPENING CASE STUDY QUESTIONS
It Takes A Village to Write an Encyclopedia
• Wikipedia and the five common
characteristics of high quality information
– Timeliness – Wikipedia’s information must be
timely. If users are receiving old and outdated
entries, or no entries for a new topic, they will not
continue using Wikipedia. An encyclopedia that is
outdated is not very useful.
– Accuracy – Wikipedia’s entries must be accurate,
and if they are inaccurate the users can change
the definition to ensure it is accurate. An
encyclopedia that is inaccurate is useless.
6-58
OPENING CASE STUDY QUESTIONS
It Takes A Village to Write an Encyclopedia
– Consistency – Wikipedia’s results must be
consistent. Users will not trust the system if it
provides different definitions for the same entry.
An encyclopedia that offers inconsistent terms is
not useful.
– Completeness – Wikipedia’s entry results need to
be complete. An encyclopedia that does not
contain vast amounts of information is not useful.
– Uniqueness – Wikipedia’s customers want unique
answers to each entry. Multiple answers to a term
will confuse the customer and they will not be able
to know which answer is correct. An encyclopedia
cannot have multiple answers for each term.
6-59
OPENING CASE STUDY QUESTIONS
It Takes A Village to Write an Encyclopedia
• How is Wikipedia resolving the issue of poor
information?
– Wikipedia originally allowed unrestricted access so that
people could contribute to the site without undergoing a
registration process.
– As with any database management system, governance is a
key issue. Without governance, there is no control over how
information is published and maintained. But as Websites like
Wikipedia grow in volume, it will be nearly impossible to
govern them.
– Wikipedia began tightening its rules for submitting entries
following the disclosure that it ran a piece falsely implication a
man in the Kennedy assassination. Wikipedia now requires
users to register before they can create articles.
6-60
OPENING CASE STUDY QUESTIONS
It Takes A Village to Write an Encyclopedia
• Why is database technology so important to
Wikipedia’s business model?
– Without databases, Wikipedia simply would not exist for
two primary reasons.
– First, vast amounts of information are at the heart of
Wikipedia and without databases it would be impossible
to store and retrieve the information. This is the
information that Wikipedia’s customers are editing and
researching.
– Second, Wikipedia uses database to store its indexes
and to find and retrieve the information that its customers
are looking for.
SECTION 6.2
DATA WAREHOUSE
FUNDAMENTALS
McGraw-Hill/Irwin
©2009 The McGraw-Hill Companies, All Rights Reserved
6-62
HISTORY OF DATA WAREHOUSING
• Bill Inmon, is recognized as the "father of the
data warehouse" and co-creator of the
"Corporate Information Factory.“
• In the 1990’s executives became less
concerned with the day-to-day business
operations and more concerned with overall
business functions
• The data warehouse provided the ability to
support decision making without disrupting the
day-to-day operations
6-63
HISTORY OF DATA WAREHOUSING
• Data warehouses extend the transformation
of data into information
• In the 1990’s executives became less
concerned with the day-to-day business
operations and more concerned with overall
business functions
• The data warehouse provided the ability to
support decision making without disrupting
the day-to-day operations
6-64
DATA WAREHOUSE FUNDAMENTALS
• Data warehouse – a logical collection of information –
gathered from many different operational databases – that
supports business analysis activities and decision-making
tasks
• The primary purpose of a data warehouse is to aggregate
information throughout an organization into a single
repository for decision-making purposes
– Database store information for a single application whereas a
data warehouse stores information from multiple databases, or
multiple applications, and external information such as
industry information
• This enables cross-functional analysis, industry analysis, market
analysis, etc., all from a single repository
– Data warehouses support online analytical processing (OLAP)
6-65
DATA WAREHOUSE FUNDAMENTALS
• Extraction, transformation, and loading (ETL)
– a process that extracts information from
internal and external databases, transforms the
information using a common set of enterprise
definitions, and loads the information into a data
warehouse
• Data mart – contains a subset of data
warehouse information
– The ETL process also gathers data from the data
warehouse and passes it to the data marts
6-66
DATA WAREHOUSE FUNDAMENTALS
• The data warehouse modeled in the next slide
compiles information from internal databases or
transactional/operational databases and external
databases through ETL
• It then send subsets of information to the data
marts through the ETL process
• Difference between a data warehouse and a data
mart?
– A data warehouse has an enterprisewide organizational
focus, while a data mart focuses on a subset of
information for a given business unit such as finance
6-67
DATA WAREHOUSE FUNDAMENTALS
6-68
Multidimensional Analysis
• Databases contain information in a series of
two-dimensional tables
• In a data warehouse and data mart, information
is multidimensional, it contains layers of
columns and rows
– Dimension – a particular attribute of information –
such as Products, Promotions, Stores, Category,
Region, Stock price, Date, Time, Weather
• The ability to look at information from different
dimensions can add tremendous business
insight
– By slicing-and-dicing the information a business can
uncover great unexpected insights
6-69
Multidimensional Analysis
• Cube – common term for the representation
of multidimensional information
6-70
Multidimensional Analysis
• Users can slice and dice the cube to drill down into
the information
– Cube A represents store information (the layers),
product information (the rows), and promotion
information (the columns)
– Cube B represents a slice of information
displaying promotion II for all products at all
stores
– Cube C represents a slice of information
displaying promotion III for product B at store 2
6-71
Multidimensional Analysis
• Data mining – the process of analyzing data to
extract information not offered by the raw data
alone
– Data mining can begin at a summary information level
(coarse granularity) and progress through increasing
levels of detail (drilling down), or the reverse (drilling up)
• To perform data mining users need data-mining
tools
– Data-mining tool – uses a variety of techniques to find
patterns and relationships in large volumes of
information and infers rules that predict future behavior
and guide decision making
• Data-mining tools include query tools, reporting tools,
multidimensional analysis tools, statistical tools, and intelligent
agents
6-72
Multidimensional Analysis
• What might an accountant discover through
the use of data-mining tools to drill down into
the details of all of the expense and
revenue?
– Which employees are spending the most
amount of money on long-distance phone calls
– Which customers are returning the most
products
6-73
Information Cleansing or Scrubbing
• An organization must maintain high-quality data
in the data warehouse
• What would happen if the information contained
in the data warehouse was only about 70 percent
accurate?
– Would you use this information to make business
decisions?
– Is it realistic to assume that an organization could get
to a 100% accuracy level on information contained in
its data warehouse?
• Information cleansing or scrubbing – a
process that weeds out and fixes or discards
inconsistent, incorrect, or incomplete information
6-74
Information Cleansing or Scrubbing
• Customer information exists in several operational
systems with different detail information
– Determining which contact information is accurate and correct for this
customer depends on the business process that is being executed
6-75
Information Cleansing or Scrubbing
• Standardizing Customer name from Operational Systems
6-76
Information Cleansing or Scrubbing
Typical events that occur during information cleansing
6-77
Information Cleansing or Scrubbing
• Accurate and complete information
6-78
Information Cleansing or Scrubbing
• Why do you think most businesses cannot achieve 100%
accurate and complete information?
– Some companies are willing to go as low as 20% complete just to
find business intelligence
– Few organizations will go below 50% accurate – the information is
useless if it is not accurate
• Achieving perfect information is almost impossible
– The more complete and accurate an organization wants to get its
information, the more it costs
– The tradeoff between perfect information lies in accuracy verses
completeness
– Accurate information means it is correct, while complete information
means there are no blanks
– Most organizations determine a percentage high enough to make
good decisions at a reasonable cost, such as 85% accurate and
65% complete
6-79
BUSINESS INTELLIGENCE
• Technology
– Even the smallest company with BI software can
do sophisticated analyses today that were
unavailable to the largest organizations a
generation ago. The largest companies today
can create enterprise-wide BI systems that
compute and monitor metrics on virtually every
variable important for managing the company.
– Technology is the most significant enabler of
business intelligence.
6-80
BUSINESS INTELLIGENCE
• People
– Understanding the role of people in BI allows
organizations to systematically create insight and turn
these insights into actions. Organizations can improve
their decision making by having the right people making
the decisions. This usually means a manager who is in
the field and close to the customer rather than an analyst
rich in data but poor in experience.
– In recent years “business intelligence for the masses”
has been an important trend, and many organizations
have made great strides in providing sophisticated yet
simple analytical tools and information to a much larger
user population than previously possible.
6-81
BUSINESS INTELLIGENCE
• Culture
– A key responsibility of executives is to shape and
manage corporate culture. The extent to which the BI
attitude flourishes in an organization depends in large
part on the organization’s culture.
– Perhaps the most important step an organization can
take to encourage BI is to measure the performance of
the organization against a set of key indicators. The
actions of publishing what the organization thinks are
the most important indicators, measuring these
indicators, and analyzing the results to guide
improvement display a strong commitment to BI
throughout the organization
6-82
DATA MINING
• Data-mining software includes many forms of AI
such as neural networks and expert systems
6-83
DATA MINING
•
•
•
Data-mining tools apply algorithms to
information sets to uncover inherent trends
and patterns in the information
Analysts use this information to develop new
business strategies and business solutions
Common forms of data-mining analysis
capabilities include:
–
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Cluster analysis
Association detection
Statistical analysis
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Cluster Analysis
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Cluster analysis – a technique used to divide an
information set into mutually exclusive groups
such that the members of each group are as
close together as possible to one another and the
different groups are as far apart as possible
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Consumer goods by content, brand loyalty or similarity
Product market typology for tailoring sales strategies
Retail store layouts and sales performances
Corporate decision strategies using social preferences
CRM systems depend on cluster analysis to
segment customer information and identify
behavioral traits
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Association Detection
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Association detection – reveals the degree to
which variables are related and the nature and
frequency of these relationships in the information
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Maytag uses association detection to ensure that each
generation of appliances is better than the previous
generation
Maytag’s warranty analysis tool automatically detects
potential issues, provides quick and easy access to
reports, and performs multidimensional analysis on all
warranty information
Market basket analysis – analyzes such items as
Web sites and checkout scanner information to detect
customers’ buying behavior and predict future behavior
by identifying affinities among customers’ choices of
products and services
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Statistical Analysis
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Statistical analysis – performs such
functions as information correlations,
distributions, calculations, and variance
analysis
– Forecast – predictions made on the basis
of time-series information
– Time-series information – time-stamped
information collected at a particular
frequency
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Statistical Analysis
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Kraft uses statistical analysis to assure consistent
flavor, color, aroma, texture, and appearance for all of
its lines of foods
Kraft evaluates every manufacturing procedure, from
recipe instructions to cookie dough shapes and sizes to
ensure that the billions of Kraft products that reach
consumers each year taste great (and the same) with
every bite
Nestle Italiana uses data mining and statistical analysis
to determine production forecasts for seasonal
confectionery products
The company’s data-mining solution gathers, organizes,
and analyzes massive volumes of information to
produce powerful models that identify trends and predict
confectionery sales
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Mining the Data Warehouse
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Ben & Jerry’s tracks the ingredients and
life of each pint in a data warehouse. If a
consumer calls in with a complaint, the
consumer affairs staff matches up the
pint with which supplier’s milk, eggs, or
cherries, etc. did not meet the
organization’s near-obsession with
quality.
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BI at Harrah’s
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The Total Rewards program allows Harrah’s to give
every single customer the appropriate amount of
personal attention, whether it’s leaving sweets in the
hotel room or offering free meals.
– Total Rewards works by providing each customer
with an account and a corresponding card that the
player swipes each time he or she plays a casino
game. The program collects information, via a
database, on the amount of time the customers
gamble, their total winnings and losses, and their
betting strategies.
•
Customers earn points based on the amount of time they
spend gambling, which they can then exchange for comps
such as free dinners, hotel rooms, tickets to shows, and
even cash.
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BI at Harrah’s
– Without database integration among its
hotels and casinos, Harrah’s would be
unable to determine what a customer’s true
value is to the company.
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For example, a customer that spend $500,000
dollars at one casino might be treated like
royalty. This same customer could visit another
Harrah’s location, but since the information is not
integrated, the new location would have no idea
that they had a high-rolling customer on the
premises and they might not treat the customer
accordingly.