Transcript MIS 451 Building Business Intelligence Systems

Acct 6910
Building Business Intelligence Systems
Class Introduction –
From Data to Knowledge
Business Intelligence
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We are drowning in data, but starving for
knowledge
Business intelligence (BI) is knowledge extracted
from data to support better business decision
making.
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Data, Information, Knowledge
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Data is a set of discrete, objective facts about
events. Ex., Mark’s GPA is 2.9 in Fall 2001.
Information is meaningful data. Ex., how is
Mark’s performance in Fall 2001?
Knowledge is hidden patterns extracted from
data. Ex., how to improve Mark’s academic
performance?
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Data, Information, Knowledge
Online bookstore Example:
July’s revenue is
$2 million
Information
July’s sale is
bad.
Knowledge
Suggest marketing
strategy to boost
sales
Data
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Building BI Systems
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Data Warehouse: A huge and integrated data
base.
Data mining: Techniques to extract hidden
patterns from data.
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What’s the Excitement About Data
Warehouse?
The top three most important technologies ranked
by IT managers in 2000-2001 (Recent surveys by
The Data Warehousing Institute and Deloitte
Research)
1.
2.
3.
Internet
Data warehouse
E-commerce
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What’s the Excitement About Data
Mining?
10 emerging technologies that will change the
world (MIT’s Magazine of Innovation, 2001 Annual
Innovation Issue)
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Brain-machine interfaces
Flexible transistors
Data mining
Digital rights
management
Biometrics
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Natural language
processing
Microphotonics
Untangling code
Robot design
Microfluidics
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Data Mining Applications
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Finance and Insurance
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Marketing: Target Marketing, Cross Selling
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E-commerce: personalization,
recommendation, web site design
Crime Detecting
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Course Objectives
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Concept Learning
Hands on experience
Real world oriented learning
Promoting data warehouse and data mining
career interests and opportunities
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Course Structure
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Data Warehouse
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Logical design of data warehouse
Physical design of data warehouse
Data preparation and staging
Data analysis (OLAP)
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Course Structure
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Data Mining
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Association rules – Cross Selling
Clustering – Target Marketing
Classification – Credit Card Approval
Advanced issues – web mining, personalization
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