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Chapter 1 The Database Environment. Jason C. H. Chen, Ph.D. Professor of MIS School of Business Administration Gonzaga University Spokane, WA 99258 chen@gonzaga.edu. COURSE. STUDENT. BOOK COPY. BOOK. a. Many-to-many:. SECTION. COURSE. SECTION. ROOM. INSTRUCTOR. COURSE.

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chapter 1 the database environment

Chapter 1 The Database Environment

Jason C. H. Chen, Ph.D.

Professor of MIS

School of Business Administration

Gonzaga University

Spokane, WA 99258

chen@gonzaga.edu

slide2

COURSE

STUDENT

BOOK COPY

BOOK

a. Many-to-many:

SECTION

COURSE

SECTION

ROOM

INSTRUCTOR

COURSE

b. One-to-many:

c. One-to-many:

d. One-to-many:

e. Many-to-many:

1. Examples of the relationships:

slide3

#8

  • one-to-many
  • one-to-many
  • There could be a relationship between customer and store. (It would be useful if the customer had never purchased a pet, so for example the store could send mailings to prospective customers.)
slide4

12.

a. Enterprise Data Model

slide5

#12- b. Would your business school or academic unit benefit from a multiple-tiered architecture for data? Why or why not?

Yes, and we should consider a multiple-tiered architecture for using a multi-tier architecture: Since much of the data may be updated from a large number of different functions, network traffic will be an issue of crucial importance.

Processing close to the source data could reduce network traffic. Client technologies however, can be mixed (personal computers with Intel or Motorola processors, network computers, information kiosks, etc.) and yet, share common data. In addition, you can change technologies at any tier with limited impact on the system modules on other tiers. All this will allow for data consistency and maintaining academic standards — a critical success factor for the academic unit.

slide6

17. User views of organizational data:

  • A good approach in developing this problem might be to carefully select the views to be developed by using the example of Figure 1-3a by collecting a transaction slip, monthly statement (representing each type of account), statement of earnings, etc. Examples of data included in each message are customer information, bank information, transaction data (checks, deposits, service charges, maintenance fees, overdraft protection fees, and so forth). Statement and deposit slip views are given below, as is the combined conceptual data model. Combining the different views could lead to adding new attributes, and possibly entities and relationships not shown in the original views.
slide7

BRANCH

TELLER

assigned

to

enters

processed by

affects

TRANSACTION

ACCOUNT

incurs

CUSTOMER

ACCOUNT

owns

belongs to

incurs

affects

TRANSACTION

TYPE

TRANSACTION

identified as

classifies

17 a) Statement View

b) Deposit Slip View

slide8

processed by

enters

BRANCH

employs

TELLER

CUSTOMER

ACCOUNT

owns

assigned

to

belongs to

incurs

affects

TRANSACTION

TYPE

TRANSACTION

identified as

classifies

17 c) Conceptual Data Model