Transcript Database Principles & Design By Colin Ritchie

Management Information
Systems
By Effy Oz & Andy Jones
Chapter 10: Business Intelligence
and Knowledge Management
www.cengage.co.uk/oz
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Objectives
• Explain the concepts of data mining and online
analytical processing
• Explain the notion of business intelligence and its
benefits to organizations
• Identify needs for knowledge storage and
management in organizations
• Explain the challenges in knowledge management
and its benefits to organizations
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining and Online Analysis
• Data warehouses are useless without software
tools
• Process data into information
• Business intelligence (BI): information gleaned
with information tools
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining
• Data mining: selecting, exploring, and modeling
data
– Supports decision making
– Finds relationships and ratios within data
– Finds unknown relationships
• Queries are more complex than traditional
• Combination of data-warehouse and data-mining
facilitates predictions
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining (continued)
• Data mining has four objectives
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Sequence or path analysis
Classification
Clustering
Forecasting
• Techniques applied to various fields
– Marketing
– Fraud detection
– Marketing to individual
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining (continued)
• Data mining can predict customer behaviour
– Banking
• Find profitable customers
• Find patterns of fraud
– Mobile phones
• Customers tend to switch companies often
• Customer loyalty programs ensure steady flow
of customer data
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining (continued)
• Utilizing loyalty programs
– Frequent flier
– Consumer clubs
– Amass huge amount of data about customer
• Harrah’s Entertainment Inc.
– Uses data mining to discern big spenders
– Allows sales agents to charge big spenders less
money
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Data Mining (continued)
• Inferring demographics
– Predict what customers likely to purchase in future
– Amazon.com
• Age ranges estimated from purchase history
• Advertises for appropriate age group
• Anticipates holidays
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Online Analytical Processing
• Online analytical processing (OLAP):
application to exploit data warehouses
– Extremely fast response
– View combinations of two dimensions
– Drilling down: start with broad info and get
more specific
– Can receive info in numbers or percentages
– Uses specifically tailored data or relational
database
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Online Analytical Processing (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Online Analytical Processing
(continued)
• OLAP application composes tables immediately
• Dimensional database: data organized into tables
– Tables show information in summaries
• Companies sell multidimensional database
packages
• OLAP applications are powerful tools for
executives
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Online Analytical Processing (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Online Analytical Processing
(continued)
• Ruby Tuesday restaurant chain case
– One location was performing below average
– Customers were waiting longer than normal
– Appropriate changes were made
• OLAP applications installed on special server
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Online Analytical Processing
(continued)
• OLAP faster than relational applications
• OLAP increasingly used by corporations
– Office Depot used OLAP on data warehouse
– CVS let 2,000 employees run analyses
– Ben & Jerry’s track ice cream popularity
• BI software becoming easier to use
• Intelligent interfaces
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
More Customer Intelligence
• Major effort of business is BI collection
• Data-mining and OLAP software integrated into
CRM
• Web becoming popular for transactions
• Targeted marketing better than mass marketing
– Data from customer not complete
– Third party companies hired to study consumer
• Doubleclick
• Engage
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
More Customer Intelligence (continued)
• Third party consumer data collection companies
– Compile billions of clickstreams to create
behavioural models
– Keep track of various fields
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Time of surfing
Frequency of visits
Which sites
Number of times ads are clicked
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Executive Dashboards
• Dashboard: interface between BI tool and user
– Resembles a car dashboard
– Contains visual images
– Designed to quickly represent specific data
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Executive Dashboards (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Knowledge Management
• Companies should record experience with
clients
• Financial transactions information not enough
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Ease of interaction
Strengths
Weaknesses
Types of problems encountered
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Knowledge Management (continued)
• Knowledge management (KM)
– Purpose is to know where to find information
about subject
– Transfer individual knowledge into databases
– Filter relevant knowledge
– Organize knowledge for easy access
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Capturing and Sorting Organizational
Knowledge
• Knowledge workers: research, prepare, and
provide information
– Much overlap in work they do
• Money saved by collecting and organizing
knowledge gained by workers
– Require workers to create reports of findings
– Require reports about sessions with clients
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Capturing and Sorting Organizational
Knowledge (continued)
• Challenge is how to find answers to specific
questions
• Software tools exist to help
• Electronic Data Systems Corp
• Replaced questionnaires with automated
system
• Motorola uses application that pulls
information from KM program
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Employee Knowledge Networks
• Some tools direct employees to other employees
• Expert can provide non-recorded expertise
• No need to waste money hiring experts in every
department
• Learning from past mistakes saves money
• Employee knowledge network: facilitate
knowledge sharing through intranets
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Employee Knowledge Networks
(continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Employee Knowledge Networks
(continued)
• Tacit Systems
– Used tool to process business communications
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Discovered work focus of employees
Expertise
Business relationships
Mines unstructured data to build profiles
Profile accessible by other employees but not private
info
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Employee Knowledge Networks
(continued)
• AskMe
– Used software to detect keywords from e-mail and
documents created
• Created knowledge base
• Allowed for search query on Web
• Search returns names of employees
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Knowledge from the Web
• Consumers post opinions of products on Web
– On vendor’s site
– Product evaluation sites
• Epinions.com
– Blogs
• Opinions expressed on large number of Web
pages
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Knowledge from the Web (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Knowledge from the Web (continued)
• Consumer opinions highly unstructured
– Garnering this knowledge could aid market
research
– Learn about competitors and own products
• Companies have developed software to get this
information
– Accenture Technology Labs
• Uses Online Audience Analysis software
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Knowledge from the Web (continued)
• Companies use tools that search Web sites for
information about products
• Data mining used to help locate what
consumers are saying about company products
• Factiva is software tool that gathers such info
– Collects from newspapers, journals, market
data, and newswires
– Screens all new information for info relevant to
specific organization
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Summary
• Business intelligence (BI) is any information
about organization, customers, or suppliers
• Data mining is selecting, exploring, and
modeling data
• Data mining useful for predicting customer
behavior and detecting fraud
• Online analytical processing (OLAP) puts data
into two-dimensional tables
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Summary (continued)
• OLAP uses dimensional databases or
calculates tables on the fly
• Drilling down means moving from a broad to
specific view of information
• Executive dashboards interface with BI
software
• Knowledge management involves gathering,
organizing, and sharing knowledge
• Main challenge of knowledge management is
identifying and classifying useful information
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning
Summary (continued)
• Most unstructured knowledge is textual
• Employee knowledge networks are software
tools to help employees find other employees
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581
© 2008 Cengage Learning