Ethics lecture slides

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Information Ethics
Information Literacy
Information Ethics
Data Analytics
Introduction to Data Analytics & Business Intelligence
Business
Intelligence
Quality
Information
Functions
5-Component
SDLC
Info Literacy
Ethics
Design
• Spreadsheet*
• Database
Data
Analytics
Big Data*
Methods
•
•
•
•
•
Data Mining*
Text Mining*
OLAP*
Visualization*
Query
Database
Benefits 
Components 
Implement with:
* Excel
 Access
Ethics & Analytics
Information
Literacy
component
Information
Ethics
one process
Data Analytics
Information Ethics Objectives
• List and explain the three steps of information literacy
• Explain how information literacy can improve problem
solving & decision making
• Define and recognize examples of ethical information
dilemmas
• Identify three standards that may govern your actions
regarding information ethics & contrast the
consequences of using each
• Describe four types of data analytics.
Segment A
Information Literacy
Information Literacy
• Define what information is needed
• Define what data is needed
• Know how and where to obtain data
• Define what processes are needed to turn data
into information
• Understand meaning of information
• Act appropriately based on information
(use information legally and ethically)
Information Literacy Example
At a local convenience store, diaper sales on
Friday evening accounted for a large percentage
of total diaper sales for the week.
1. No particular brand, size or type of diaper
accounted for the increase.
2. Diaper sales for the rest of the week were
unaffected by Friday evening’s sales volume.
3. No other products in the store had a similar
trend.
4. This trend had been going on since the store
opened.
You are the store manager.
Your job is to maximize profits.
Segment B:
Information Ethics
Ethical Information Dilemmas
• Misrepresent Data
• Fabricate Data
• Conceal Information
• Acquire Unauthorized Information
• Misdirected Information
Guidance for Business Professionals
• Laws
• Corporate Policy
• Ethical Behavior
Misdirected Information Scenario #1
Suppose you are buying a condo and you
know that at least one other party is bidding
against you. While agonizing over your best
strategy, you stop at a local Starbucks. As you
sip your latte, you overhear a conversation at
the table next to yours. Three people are
talking loudly enough that it is difficult to
ignore them, and you soon realize that they
are the real estate agent and the couple who
is competing for the condo you want. They
are preparing their offer.
Misdirected Information Scenario #2
Consider the same situation from a different
perspective – instead of overhearing the
conversation, suppose you receive that same
information in an email. Perhaps an
administrative assistant at the agent’s office
confuses you and the other customer and
mistakenly sends you the terms of the other
party’s offer.
Misdirected Information Scenario #3
Suppose that you sell computer software. In
the midst of a sensitive price negotiation,
your customer accidentally sends you an
internal email that contains the maximum
amount that the customer can pay for your
software.
How Will You Handle
Misdirected Information?
• Ethical and legal are not synonymous.
• Establish your personal policy about dealing
with information that is misdirected to you.
Segment C:
Data Analytics
Types of Data Analytics
Slide courtesy of Richard Gomes, PriceWaterhouseCoopers
TrueFit
House of Fraser - http://www.truefit.com/about-us/how_it_works
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