INFO 340

1. INFO 340 Lecture 1 Class Overview File based systems

2. Introduction/Logistics • Attendance • Introduction • Instructor • Chuck Benson • cabenson@washington.edu • 206-616-6937 • Schedule & Location • Mon & Wed 4:00 – 5:50 pm, MGH 234 • Mon (Lab) 11:30am – 12:20 pm, MGH 430 • Office hours: TBD • Syllabus • On web site staff.washington.edu/cabenson/INFO_340

3. Introduction/Logistics (continued) • Textbook - Database Systems - Connolly & Begg • Grading/Assessment • Homework & Pop Quizzes – 30% • Midterm – 20% • Group Project – 30% • Final – 20% • All assignments due at beginning of class

4. Introduction/Logistics (continued) • E-mail guidelines • Will try to respond within 24 hours • Don’t hold up an assignment waiting for me to respond • Please put [INFO 340] in the subject line • When appropriate, use the class listserve (info340a_wi09@u.washington.edu)

5. Learning - Big Picture Objectives • Develop a conceptual understanding of relational database systems • Develop a conceptual understanding of information retrieval systems • Develop skill set in working with database and information retrieval tools

6. My background • Manager of Technology Services – Health Sciences • BE Electrical Engineer, MS Computer Science • Started & operated Assistive Tech Business • Healthcare & Biotech fields

7. Database Systems & Information Retrieval Systems • This quarter • Look at similarities & differences • Learn some tools in both • Do a class project incorporating both • Some of the tools & technologies: • MySQL • Java • Lucene

8. What is a database? • Method to store data in a structured way • We want it to be able to: • Add data • Retrieve data • Update data • Share data • Combine it • Compare it • Do math or other functions on it

9. Barcodes & Databases shift power balance • Commercially introduced in the 1960’s • Power-balance between manufacturers and retailers (supermarkets) was with manufacturers • Mass advertising campaigns controlled information reaching consumer • Companies such as Gillette would run massive marketing cycles w/ad compaigns to “pull” consumers through supermarket aisles • Supermarkets were not in a position to say no • The Gillette sales rep could largely • Dictate how many blades the store would buy • What types • How they would be displayed • When they would be delivered • Often could dictate what the price would be From Alvin Toffler’s PowerShift

10. Gillette Consumer Retailer • Gillette controlled information flow going both ways • They controlled information to the consumer via advertising, product launch dates, product pricing • For another similar mega-company, Campbell’s Soup, there was a time when phone numbers were not even listed on their business cards • They didn’t need to be • There wasn’t much to talk about -- they weren’t going to negotiate anything

11. In mid-60’s, a committee of retailers, wholesalers & grocery manufacturers met companies like IBM & NCR to address: • Long checkout lines • Errors in accounting • Result was the UPC (Universal Product Code) or ‘Barcode’ and the supporting backend database

12. Transfer of Power • In addition to solving the accounting and long line issues, the barcode and associated database system transferred power from the manufacturer to the retailer • Over 50,000 items in average supermarket today (up from ~15,000 in 1980)

13. Retailer now knows: • What sold • To include preferences over other items (ie 2% milk instead of whole milk) • Size of item • Quantity of item • When it sold • What else sold with it • Total of bill • Associations -- ie magazine with ads that is purchased by a person that buys this product • Potentially free shelf space • Competitor product sales info • Profile of the buyer (ie w/discount cards) • Retailers and their buyers can use this data to immediately determine profitability for each item • Retailer now determines where products are placed -- directly affecting their sellability • Retailer now tells the manufacturer to pay “push money” to get their products placed in desirable locations

14. To do this, the retailer needed to: • Collect the data • Store the data • Update the data • Aggregate the data • Query the data • Write reports with the data • Do statistical analysis with the data

15. Another example - iTunes • When first released, why did iTunes work in an age of free music such as Napster • Why were people willing to pay $1 a song?

16. Break up into groups of 3 - 4 & take 15 minutes to: • List the information that iTunes tracks/needs to keep up with -- ie song, artist, etc • List the things that iTunes store must do -- ie authenticate user, check credit, etc. • Have a written list per group ready

17. Resources • Marion Nestle "The soft sell: how the food industry shapes our diets".Nutrition Action Healthletter. Sept 2002. FindArticles.com. 12 Sep. 2006. http://www.findarticles.com/p/articles/mi_m0813/is_7_29/ai_90980246

18. Assignment • Read Chapter 2 of Connolly & Begg • Get your book if you don’t have it!