Data repository, Research commercial data repositories.
Amandla! A Revolution in Four Part Harmony (2003) Lee Hirsch
August 7, 2017Comparing and Contrasting Literary
August 7, 2017
Data repository, Research commercial data repositories.
Brochure
In this writing assignment, you will create a brochure advertising your services as a data repository.
Research commercial data repositories, be sure to understand this business model, including the services, benefits, and marketing of services.
Use a publisher program to create a two-page, two-fold brochure. If you are using a word processing program, you may create a two-page, two column document to create your brochure. Address the following in your brochure:
• You are advertising your services as a commercial data repository to existing businesses.
• Include your services, customer benefits, and reasons to do business with you.
• Provide at least three reasons why the customer should be collecting data.
• Include at least one graphic or picture of your choosing.
Reference:
Kroenke, D. M. (2013). Using MIS (5th ed.). Upper Saddle River, NJ: Prentice Hall.
Chapter 5 & 9
Using MIS 5e
Chapter 9
Business Intelligence
Systems
by David Kroenke
“We’re Sitting On All This Data. I Want to
Make It Pay.”
Anne wants membership data to:
• Combine membership data and publicly
available data
• Enable target marketing
• Increase wedding revenue
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 typical reporting applications?
Q5: How do organizations use typical data mining
applications?
Q6: What is the role of knowledge management systems?
Q7: What are the alternatives for publishing business
intelligence?
Q8: 2022?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-3
Q1: How Do Organizations Use
Business Intelligence (BI) Systems?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-4
Example Uses of Business Intelligence
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-5
Q2: What Are the Three Primary Activities
in the Business Intelligence Process?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-6
Using BI for Problem-solving at GearUp:
Process and Potential Problems
1. Obtain commitment from vendor
2. Run sales event
3. Sell as many items as possible
4. Order amount actually sold
5. Receive partial order and damaged items
6. If received less than ordered, ship partial
order to customers
7. Some customers cancel orders
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-7
Tables Used for BI Analysis at GearUp
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-8
GearUp Analysis: Item Summary and
Lost Sales Summary Reports
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-9
Short and Damaged Shipments Details
Report
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-10
Publish Results
Options
• Print and distribute via email or
collaboration tool
• Publish on Web server or SharePoint
• Publish on a BI server
• Automate results via Web service
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-11
Q3: How Do Organizations Use Data
Warehouses and Data Marts to
Acquire Data?
• Why extract operational data for BI
processing?
? Security and control
? Operational not structured for BI analysis
? BI analysis degrades operational server
performance
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-12
Components of a Data Warehouse
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-13
Examples of Consumer Data that Can
Be Purchased
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-14
Possible Problems with Operational
Data
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-15
Data Warehouses vs. Data Marts
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-16
Q4 How Do Organizations Use Typical
Reporting Applications
Basic operations:
1. Sorting
2. Filtering
3. Grouping
4. Calculating
5. Formatting
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-17
Example RFM Scores
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-18
Example of Drilling Down into Expanded
Grocery Sales OLAP Report
Figure 9-17
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-19
Drilling Down to Expanded Grocery
Store Sales
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-20
Using MIS InClass 9 – A Group Exercise
Do You Have a Club Card?
Acxiom Corporation — a data aggregator
•Visit www.acxiom.com.
• Navigate Web site and make a list of 10
different products Acxiom provides.
• Describe Acxiom’s top customers.
• Describe the kinds of data Acxiom must
collect to be able to provide these products
to its customers.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-21
Q5 How Do Organizations Use Typical
Data-mining Applications?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-22
Unsupervised vs. Supervised Data
Mining
Unsupervised Supervised
•No model before •Model created before
running analysis analysis
•Hypotheses created •Hypotheses created
after analysis before analysis
•Cluster analysis to find •Regression analysis:
groups make predictions
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-23
Neural Networks
• Used for predicting values and making
classifications
• Complicated set of nonlinear equations
• Go to http://kdnuggets.com and search for
“neural network”
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-24
Market Basket Analysis at a Dive Shop
(Transactions = 400)
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-25
Decision Tree Example for MIS Classes
(hypothetical data)
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-26
Decision Rules
• If student is a junior and works in a
restaurant, then predict grade > 3.0.
• If student is a senior and is a nonbusiness
major, then predict grade = 3.0.
• If student is a junior and does not work in a
restaurant, then predict grade = 3.0.
• If student is a senior and is a business
major, then make no prediction.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-27
Credit Score Decision Tree
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-28
Ethics Guide: The Ethics of
Classification
Classifying applicants for college
• University collects demographics and
performance data of all its students
• Uses decision tree data mining program
• Uses statistically valid measures to obtain
statistically valid results
• No human judgment involved
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-29
Q6. What Is the Role of Knowledge
Management Systems?
1. Encourage free flow of ideas.
2. Improve customer service by streamlining
response time.
3. Boost revenues by getting products and
services to market faster.
4. Enhance employee retention rates by
recognizing and rewarding knowledge
sharing.
5. Streamline operations and reduce costs.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-30
Sharing Document Content
• Indexing — most important content function in KM
applications
• Real Simple Syndication (RSS) — subscribing to
content sources
• Blogs — place where employees share their
knowledge that may include RSS feeds
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-31
Expert Systems
Encode human knowledge as Rule-based
systems (IF/THEN)
Rules created by interviewing experts
Major problems with ES:
• Expensive to develop
• Unpredictable maintenance
• Over hyped
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-32
Expert System for Pharmacies
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-33
Q7 What Are the Alternatives for
Publishing Business Intelligence?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-34
Components of a Generic Business
Intelligence System
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-35
Q8: 2022
• Companies will know more about your
purchasing habits and psyche.
• Social singularity — machines can build
their own information systems.
• Will machines possess and create
information for themselves?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-36
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 & documents
3. What, if anything can be done to prevent
what Megan did?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-37
Ethics Guide: Data Mining in the Real
World
Different from way described in textbooks
Problems:
• Dirty data
• Missing values
• Lack of knowledge at start of project
• Over fitting
• Probabilistic
• Seasonality
• High risk—cannot know outcome
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-38
Active Review
Q1: How do organizations use business intelligence systems?
Q2: What are the three primary activities in the business
intelligence process?
Q3: How do organizations use data warehouses and data
marts to acquire data?
Q4: How do organizations use typical reporting applications?
Q5: How do organizations use typical data mining
applications?
Q6: What is the role of knowledge management systems?
Q7: What are the alternatives for publishing business
intelligence?
Q8: 2022?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-39
Case Study 9: THL
Leasing camper vehicles has three fundamental
phases:
1. Matching customer requirements with vehicle
availability
2. Reserving vehicles and operations support
3. Billing and customer service
• Online Reservation System
• Business Intelligence Information System
• OLAP
Using MIS 5e
Chapter 9
Business Intelligence
Systems
by David Kroenke
“We’re Sitting On All This Data. I Want to
Make It Pay.”
Anne wants membership data to:
• Combine membership data and publicly
available data
• Enable target marketing
• Increase wedding revenue
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-2
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 typical reporting applications?
Q5: How do organizations use typical data mining
applications?
Q6: What is the role of knowledge management systems?
Q7: What are the alternatives for publishing business
intelligence?
Q8: 2022?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-3
Q1: How Do Organizations Use
Business Intelligence (BI) Systems?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-4
Example Uses of Business Intelligence
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-5
Q2: What Are the Three Primary Activities
in the Business Intelligence Process?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-6
Using BI for Problem-solving at GearUp:
Process and Potential Problems
1. Obtain commitment from vendor
2. Run sales event
3. Sell as many items as possible
4. Order amount actually sold
5. Receive partial order and damaged items
6. If received less than ordered, ship partial
order to customers
7. Some customers cancel orders
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-7
Tables Used for BI Analysis at GearUp
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-8
GearUp Analysis: Item Summary and
Lost Sales Summary Reports
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-9
Short and Damaged Shipments Details
Report
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-10
Publish Results
Options
• Print and distribute via email or
collaboration tool
• Publish on Web server or SharePoint
• Publish on a BI server
• Automate results via Web service
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-11
Q3: How Do Organizations Use Data
Warehouses and Data Marts to
Acquire Data?
• Why extract operational data for BI
processing?
? Security and control
? Operational not structured for BI analysis
? BI analysis degrades operational server
performance
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-12
Components of a Data Warehouse
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-13
Examples of Consumer Data that Can
Be Purchased
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-14
Possible Problems with Operational
Data
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-15
Data Warehouses vs. Data Marts
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-16
Q4 How Do Organizations Use Typical
Reporting Applications
Basic operations:
1. Sorting
2. Filtering
3. Grouping
4. Calculating
5. Formatting
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-17
Example RFM Scores
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-18
Example of Drilling Down into Expanded
Grocery Sales OLAP Report
Figure 9-17
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-19
Drilling Down to Expanded Grocery
Store Sales
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-20
Using MIS InClass 9 – A Group Exercise
Do You Have a Club Card?
Acxiom Corporation — a data aggregator
•Visit www.acxiom.com.
• Navigate Web site and make a list of 10
different products Acxiom provides.
• Describe Acxiom’s top customers.
• Describe the kinds of data Acxiom must
collect to be able to provide these products
to its customers.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-21
Q5 How Do Organizations Use Typical
Data-mining Applications?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-22
Unsupervised vs. Supervised Data
Mining
Unsupervised Supervised
•No model before •Model created before
running analysis analysis
•Hypotheses created •Hypotheses created
after analysis before analysis
•Cluster analysis to find •Regression analysis:
groups make predictions
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-23
Neural Networks
• Used for predicting values and making
classifications
• Complicated set of nonlinear equations
• Go to http://kdnuggets.com and search for
“neural network”
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-24
Market Basket Analysis at a Dive Shop
(Transactions = 400)
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-25
Decision Tree Example for MIS Classes
(hypothetical data)
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-26
Decision Rules
• If student is a junior and works in a
restaurant, then predict grade > 3.0.
• If student is a senior and is a nonbusiness
major, then predict grade = 3.0.
• If student is a junior and does not work in a
restaurant, then predict grade = 3.0.
• If student is a senior and is a business
major, then make no prediction.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-27
Credit Score Decision Tree
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-28
Ethics Guide: The Ethics of
Classification
Classifying applicants for college
• University collects demographics and
performance data of all its students
• Uses decision tree data mining program
• Uses statistically valid measures to obtain
statistically valid results
• No human judgment involved
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-29
Q6. What Is the Role of Knowledge
Management Systems?
1. Encourage free flow of ideas.
2. Improve customer service by streamlining
response time.
3. Boost revenues by getting products and
services to market faster.
4. Enhance employee retention rates by
recognizing and rewarding knowledge
sharing.
5. Streamline operations and reduce costs.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-30
Sharing Document Content
• Indexing — most important content function in KM
applications
• Real Simple Syndication (RSS) — subscribing to
content sources
• Blogs — place where employees share their
knowledge that may include RSS feeds
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-31
Expert Systems
Encode human knowledge as Rule-based
systems (IF/THEN)
Rules created by interviewing experts
Major problems with ES:
• Expensive to develop
• Unpredictable maintenance
• Over hyped
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-32
Expert System for Pharmacies
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-33
Q7 What Are the Alternatives for
Publishing Business Intelligence?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-34
Components of a Generic Business
Intelligence System
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-35
Q8: 2022
• Companies will know more about your
purchasing habits and psyche.
• Social singularity — machines can build
their own information systems.
• Will machines possess and create
information for themselves?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-36
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 & documents
3. What, if anything can be done to prevent
what Megan did?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-37
Ethics Guide: Data Mining in the Real
World
Different from way described in textbooks
Problems:
• Dirty data
• Missing values
• Lack of knowledge at start of project
• Over fitting
• Probabilistic
• Seasonality
• High risk—cannot know outcome
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 9-38
Active Review
Q1: How do organizations use business intelligence systems?
Q2: What are the three primary activities in the business
intelligence process?
Q3: How do organizations use data warehouses and data
marts to acquire data?
Q4: How do organizations use typical reporting applications?
Q5: How do organizations use typical data mining
applications?
Q6: What is the role of knowledge management systems?
Q7: What are the alternatives for publishing business
intelligence?
Q8: 2022?
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Chapter 9-39
Case Study 9: THL
Leasing camper vehicles has three fundamental
phases:
1. Matching customer requirements with vehicle
availability
2. Reserving vehicles and operations support
3. Billing and customer service
• Online Reservation System
• Business Intelligence Information System
• OLAP
