MIS5101 Week 13 Security Privacy Data Mining
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share

MIS5101 Week 13 Security Privacy Data Mining

  • 1,235 views
Uploaded on

Slides from week 13 of MIS5101: Business Intelligence taught by Prof. Steven L. Johnson at Temple University Fox School of Business.

Slides from week 13 of MIS5101: Business Intelligence taught by Prof. Steven L. Johnson at Temple University Fox School of Business.

More in: Education , Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
1,235
On Slideshare
737
From Embeds
498
Number of Embeds
3

Actions

Shares
Downloads
12
Comments
0
Likes
0

Embeds 498

http://community.mis.temple.edu 496
https://blackboard.strayer.edu 1
http://www.docshut.com 1

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. MIS5101: Business IntelligenceWeek 13 – Security, Privacy and Data Mining PROF. STEVEN L. JOHNSON Twitter: @StevenLJohnson http://stevenljohnson.org http://community.mis.temple.edu/mis5101fall10/
  • 2. Today’s Agenda  Case Discussion  Group Project Discussion  Final Exam Review  Reading + Blog Discussion  Student Evaluation Forms  Group Project Work
  • 3. Case Analysis Discussion Questions  What business is deCODE in?  Why Iceland?  Why was the database project opposed?  What could deCODE have done differently?  What does IFA/ShopSense propose to do?  What can they learn from deCODE?  What are expert advice do you agree with? Which do you disagree with?
  • 4. 100 Second Reflection1.  What was your favorite case study this semester? Why? •  Balancing Access with Accuracy for Infant HIV Diagnostics in Tanzania •  SKOLAR, M.D.: Is There a Business for Web-Based Information for Doctors? •  Intermountain Health Care •  Global Knowledge Management at Danone •  Data.gov •  In-Vitro Fertilization (IVF): Outcomes Measurement •  deCODE Genetics: Hunting for Genes to Develop Drugs •  Dark Side of Customer Analytics2.  Any other comments?
  • 5. Group Project Presentations  Convince an audience making project funding decision:   (A) What business problem are you solving?   (B) How do you propose solving it?   (C) How will the solution provide business value?  Format   9-12 minutes + 2-4 minutes for questions  Evaluation forms   Content: Clear description of business problem   Content: Effective justification of business value   Content: Convincing discussion of project feasibility   Presentation: Delivery and pacing   Presentation: Connection with audience   Overall Impression: Assessment of project
  • 6. Exam Review: Format  Take-home: 5PM posted to class website, 8PM due via email  Open-note: no outside assistance or Internet assistance  4 short answer questions (~ 60% of grade (4 x 15% each)   Multiple bullet point answer or up to 1 paragraph answer   Ex.: “What are 3 pros and 3 cons of giving ad-hoc SQL query access?  1 essay question (~ 40% of grade)   Multi-part question or more involved question with a multi- paragraph answer required   Pick from 2 or 3 choices   Ex.: “Temple University is looking for new revenue streams. They want your advice: should they offer to sell marketers the list of student email addresses? Why or why not?”
  • 7. Reading  Why Im releasing my genetic data online   Agree or disagree?
  • 8. Blog Discussion  Personal backups and disaster recovery   Cloud computing   Device proliferation   Role of operating systems
  • 9. For More Information PROF. STEVEN L. JOHNSON EMAIL: STEVEN@TEMPLE.EDU Twitter: @StevenLJohnson http://stevenljohnson.org http://community.mis.temple.edu/mis5001fall10johnson/