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Chapter 9
Business Intelligence Systems
“We Can Make the Bits Produce Any Report You
Want, But You’ve Got to Pay for It.”
• Need to monitor patient workout data.
• Spending too many hours each day looking at patient
workout data.
• Great use for exception reporting.
• Animation & new types of reporting creates innovative and
motivating reports.
• Eliminating silos enables everyone to gain more information
from PRIDE data.
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Study Questions
Q1: How do organizations use business intelligence (BI) systems?
Q2: What are the three primary activities in the BI process?
Q3: How do organizations use data warehouses and data marts to acquire data?
Q4: How do organizations use reporting applications?
Q5: How do organizations use data mining applications?
Q6: How do organizations use BigData applications?
Q7: What is the role of knowledge management systems?
Q8: What are the alternatives for publishing BI?
Q9: 2024?
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Q1: How Do Organizations Use Business Intelligence
(BI) Systems?
Components of Business
Intelligence System
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Example Uses of Business Intelligence
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What Are Typical Uses for BI?
• Identifying changes in purchasing patterns
– Important life events cause customers to change what they buy.
• BI for entertainment
– Netflix has data on watching, listening, and rental habits, however,
determines what people actually want, not what they say.
• Predictive policing
– Analyze data on past crimes, including location, date, time, day of
week, type of crime, and related data, to predict where crimes are
likely to occur.
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Q2: What Are the Three Primary Activities in the BI
Process?
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Using Business Intelligence to Find Candidate Parts at
AllRoad
• Identified criteria for parts customers might want to print
themselves.
– Provided by vendors who already agree to make part
design files available for sale.
– Purchased by larger customers.
– Frequently ordered parts.
– Ordered in small quantities.
– Simple in design.
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Acquire Data: Extracted Order Data
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Extracted Part Data
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Analyze Data: Access Query
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Query Result
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Joining Order Extract and Filtered Parts Tables
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Sample Orders and Parts View Data
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Customer Summary
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Qualifying Parts Query Design
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Qualifying Parts Query Results Figure
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Publish Results: Sales History for Selected Parts
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Q3: How Do Organizations Use Data Warehouses and
Data Marts to Acquire Data?
Functions of a Data Warehouse
• Extract data from operational, internal and external
databases.
• Cleanse data.
• Organize, relate data warehouse.
• Catalog data using metadata.
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Components of a Data Warehouse
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Examples of Consumer Data That Can Be Purchased
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Possible Problems with Source Data
Curse of
dimensionality
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Data Warehouses Versus Data Marts
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Q4: How Do Organizations Use Reporting
Applications?
• Create meaningful information from disparate data sources.
• Deliver information to user on time.
• Basic operations:
1. Sorting
2. Filtering
3. Grouping
4. Calculating
5. Formatting
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How Does RFM Analysis Classify Customers?
• Recently
• Frequently
• Money
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RFM Analysis Classifies Customers
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Typical OLAP Report
OLAP Product Family by Store Type
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Example of Expanded Grocery Sales OLAP Report
Drill
down into
the data
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OLAP Product Family and Store Location by Store Type,
Showing Sales Data for Four Cities
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Q5: How Do Organizations Use Data Mining
Applications?
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Unsupervised Data Mining
• Analyst does not start with a priori hypothesis or model.
• Hypothesized model created based on analytical results to
explain patterns found.
• Example: Cluster analysis.
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Supervised Data Mining
• Uses a priori model to compute outcome of model
• Prediction, such as regression analysis
• Ex: CellPhoneWeekendMinutes
= (12 + (17.5*CustomerAge)+(23.7*NumberMonthsOfAccount)
= 12 + 17.5*21 + 23.7*6 = 521.7
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Market-Basket Analysis
• Market-basket analysis – a data-mining technique for
determining sales patterns.
– Statistical methods to identify sales patterns in large
volumes of data.
– Products customers tend to buy together.
– Probabilities of customer purchases.
– Identify cross-selling opportunities.
Customers who bought fins also bought a mask.
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Market-Basket Example: Dive Shop
Transactions = 400
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Decision Trees
• Hierarchical arrangement of criteria to predict a classification
or value.
• Unsupervised data mining technique.
• Basic idea of a decision tree
– Select attributes most useful for classifying something
on some criteria to create “pure groups”.
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Credit Score Decision Tree
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Decision Rules for Accepting or Rejecting Offer to
Purchase Loans
If percent past due is less than 50 percent, then accept loan.
• If percent past due is greater than 50 percent and
• If CreditScore is greater than 572.6 and
• If CurrentLTV is less than .94, then accept loan.
•
Otherwise, reject loan.
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Using MIS InClass Exercise 9: What Singularity Have
We Wrought?
Trends in the Computing Industry
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Q6: How Do Organizations Use BigData Applications?
• Huge volume – petabyte and larger.
• Rapid velocity – generated rapidly.
• Great variety
– Structured data, free-form text, log files, possibly
graphics, audio, and video.
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MapReduce Processing Summary
Google search
log broken into
pieces
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Google Trends on the Term Web 2.0
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Hadoop
• Open-source program supported by Apache Foundation2.
• Manages thousands of computers.
• Implements MapReduce
– Written in Java
• Amazon.com supports Hadoop as part of EC3 cloud offering.
• Query language entitled Pig.
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Q7: What Is the Role of Knowledge Management
Systems?
• Knowledge Management
– Creating value from intellectual capital and sharing that
knowledge with those who need that capital.
– Preserving organizational memory by capturing and
storing lessons learned and best practices of key
employees.
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Benefits of Knowledge Management
• Improve process quality.
• Increase team strength.
• Goal:
– Enable employees to use organization’s collective
knowledge.
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What Are Expert Systems?
Expert systems
Rule-based
IF/THEN
Encode human
knowledge
Expert systems shells
Process IF side
of rules
Report values of
all variables
Knowledge gathered
from human experts
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Example of IF/THEN Rules
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Drawbacks of Expert Systems
1. Difficult and expensive to develop
– Labor intensive
– Ties up domain experts
2. Difficult to maintain
– Changes cause unpredictable outcomes
– Constantly need expensive changes
3. Don’t live up to expectations
– Can’t duplicate diagnostic abilities of humans
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What Are Content Management Systems (CMS)?
• Support management and delivery of documents, other expressions of
employee knowledge
• Challenges of Content Management
– Databases are huge
– Content dynamic
– Documents do not exist in isolation
– Contents are perishable
– In many languages
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What are CMS Application Alternatives?
• In-house custom
– Customer support department develops in-house database
applications to track customer problems
• Off-the-shelf
– Horizontal market products (SharePoint)
– Vertical market applications
• Public search engine
– Google
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How Do Hyper-Social Organizations Manage
Knowledge?
• Hyper-social knowledge management
– Application of social media and related applications for
management and delivery of organizational knowledge
resources.
• Hyper-organization theory
– Framework for understanding this new direction in KM.
– Focus moves from knowledge and content per se to fostering
authentic relationships among creators and users of
knowledge.
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Hyper-Social KM
Alternative Media
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Q8: What Are the Alternatives for Publishing BI?
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Elements of a BI System
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Q9: 2024?
• World generating and storing exponentially more information.
• Information about customers, and data mining techniques going
to get better.
• Companies will know more about your purchasing habits and
psyche.
• Social singularity – Machines will build their own information
systems.
• Will machines possess and create information for themselves?
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Guide: Semantic Security
1. Unauthorized access to protected data and information
– Physical security
 Passwords and permissions
 Delivery system must be secure
2. Unintended release of protected information through
reports and documents.
3. What, if anything, can be done to prevent what Megan did?
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Guide: Data Mining in the Real World
• Problems:
– Dirty data
– Missing values
– Lack of knowledge at start of project
– Over fitting
– Probabilistic
– Seasonality
– High risk – unknown outcome
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Active Review
Q1: How do organizations use business intelligence (BI) systems?
Q2: What are the three primary activities in the BI process?
Q3: How do organizations use data warehouses and data marts to acquire data?
Q4: How do organizations use reporting applications?
Q5: How do organizations use data mining applications?
Q6: How do organizations use BigData applications?
Q7: What is the role of knowledge management systems?
Q8: What are the alternatives for publishing BI?
Q9: 2024?
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Case Study 9: Hadoop the Cookie Cutter
• Third-party cookie created by a site other than one you visited.
• Generated in several ways, most common occurs when a Web
page includes content from multiple sources.
• DoubleClick
– IP address where content was delivered.
– Records data in cookie log.
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Case Study 9: Hadoop the Cookie Cutter (cont'd)
• Third-party cookie owner has history of what was shown,
what ads clicked, and intervals between interactions.
• Cookie log contains data to show how you respond to ads
and your pattern of visiting various Web sites where ads
placed.
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FireFox Collusion
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Ghostery in Use (ghostery.com)
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