CHAPTER 9 DATABASE MANAGEMENT SYSTEMS

CHAPTER 9
DATABASE MANAGEMENT SYSTEMS
REVIEW QUESTIONS
1. Database planning, design, implementation, operation and maintenance, and change
and growth.
2. The users, the database management system, the database administrator, and the
physical database structures.
3. The primary difference between the network and hierarchical models is in the parentchild
relationship. The network model allows a child file to have multiple parents. The
hierarchical model permits a child to be associated with only one parent record.
4. a. Less data redundancy
b. Single update of data
c. Current values for all user applications
d. Task-data independence.
5. Program development, backup and recovery, database usage reporting, and
database access.
6. One level is the schema, which is the conceptual view of the data. The schema
describes the entire database, and it represents the database logically. The second
level is the internal view which is the physical arrangement of the records. At this
level, the physical data records are described as well as linkages between files. The
next level is the subschema, which is the external view of the database that specific
users have authorization to use. This is also called the user view. This is the level
that users find of most interest.
7. The primary key is a table attribute the value of which is unique to the record. It is a
unique identifier.
8. Logically related tables need to be physically connected to achieve the associations
described in the data model. This is accomplished by embedding the primary key of
one table into the related table as a foreign key.
9. The data dictionary describes every data element in the database. The data
dictionary enables all users (and programmers) to share a common view of the data
resource, thus facilitating greatly the analysis of user needs.
10. An organization has three diverse operating units: tractors, sewing machines, and
computer chips. These units have different customers, suppliers, and production
facilities. Operating data are consolidated for financial reporting only.
11. An entity is anything about which the organization wishes to capture data. Entities
may be physical, such as “Inventory”, “Customer”, or “Employee”. They may also be
conceptual, such as “Sale” (to a customer), “Accounts Receivable”, or “Accounts
Payable”.
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12. The XYZ company is a geographically distributed organization with several sites
around the country. Users at these sites need rapid access to common data for
read-only purposes.
13. (1:0,1) Every occurrence (record) in a one entity (Employee), there is a possibility of
zero or one occurrence in the related entity (Company Car).
(1:1) Describes a situation in which each record in one entity is always associated with
one (and only one) record in the associated entity. For example, a company laptop
computer is assigned to only one manager, and every manager is assigned only one
laptop.
(1:M) An example of this situation is that each item of Inventory (entity) is supplied by
one and only one Vendor (related entity), but each Vendor supplies one or many
different Inventory items to the company.
(M:M) A company with a policy of purchasing the same types of inventory from multiple
suppliers would have a M:M association between the Vendor and Inventory entities.
14. The term association pertains to the nature of the relationship between two entities.
This is represented by a verb such as shipped, requests, or receives. Cardinality is
the degree of association between two entities. Simply stated, cardinality describes
the number of possible occurrences in one table that are associated with a single
occurrence in a related table.
15. A network model allows parents to have multiple children and vice versa. A separate
linking file works by creating a file that contains pointer records in linked-list
structure. This file contains the addresses of multiple predefined links.
16. a. All occurrences at the intersection of a row and column are a single value. No
multiple values (repeating groups) are allowed.
b. The attribute values in any column must all be of the same class.
c. Each column in a given table must be uniquely named.
d. Each row in the table must be unique in at least one attribute that is considered to be
the primary key.
17. a. Restrict—Extracts rows that satisfy the given condition from a specified table
and places these rows into a new table.
b. Project—Extracts columns from a specified table and places these attributes
(columns) into a new table.
c. Join—Builds a new table from two tables consisting of all concatenated pairs of rows,
one from each table.
18. A table normalized to 3NF meets the following conditions:
1. All nonkey attributes in the table are dependent on the primary key.
2. All nonkey attributes are independent of the other nonkey attributes.
In other words, the primary key of a table wholly and uniquely defines each attribute in
the table, and none of the table attributes are defined by an attribute other than the
primary key.
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19. The user may restrict the fields of data to view with the AS SELECT command. Further,
the user may restrict the rows or records of data to be viewed with the WHERE
command. The WHERE command allows the user to view only those records that have
values which fall within a certain range for one or more fields of data.
20. A data model is the blueprint for creating the physical database. Database designers
identify system entities and prepare a model of them using a graphical
representation technique called an entity relationship (ER) diagram.
21. The deletion anomaly may cause records to be deleted unintentionally and may
occur for some time before the problem is noticed. A deletion anomaly occurs when
an item in one file is legitimately deleted. The problem occurs when this file is linked
to another file, which may also have a record deleted, due to its link. If the second
record should not be deleted, then an update anomaly has occurred.
22. A user view is the set of data that a particular user sees. Examples of user views are
computer screens for entering or viewing data, management reports, or source
documents, such as an invoice.
23. User views derive from underlying database tables. Simple views may be
constructed from a single table, while more complex views may require several
tables. Furthermore, a single table may contribute data to many different views.
24. Valid entities meet the two conditions below:
Condition 1. An entity must have two or more occurrences.
Condition 2. An entity must contribute at least one attribute that is not
provided through other entities.
25. Because attributes are the logical and relevant characteristics of an entity, they are
unique to it. Therefore, the same attribute should not be used to define two different
entities.
DISCUSSION QUESTIONS
1. In the traditional data management environment, applications are developed with
data and program dependency. Typically, these programs are application specific.
Thus, the users of the application data tend to be proprietary about the data in “their”
application and may not be amenable to sharing such data.
2. If your university were to use different databases for the registrar, library, parking,
food services, and computing services, then the number of forms you would have to
fill out, if any of your personal data changes, would be plentiful. For example, if you
were to move during the semester to a different apartment, the university should be
notified. In this situation, a couple of things could happen. You could be required to
go to each service individually and fill out an address form, or you could go to one
central location and fill out a form that has multiple copies, which are sent to the
various areas on campus for update. In any case, your address could be keyed in
correctly by the registrar. You might receive some correspondence from the registrar
and assume that the address correction was made. However, a keypunch error
might have occurred by the library staff, and you may not receive notification that
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you have a library book which you forgot about past due. After the end of the
semester, you may not receive your final grade report. When you call the registrar,
you may find out that the library has reported that you have an overdue book and
that your grades should be held until the book is returned, and the fine is paid.
3. Under the database concept, the data becomes centrally stored with many different
users accessing the database. However, each user should not have access to the
whole database. Under the traditional data management approach, where the data
are limited to a single application, the user access problem was not as much of a
threat. The DBMS is a special software system that is programmed to know which
data each user is authorized to access. This controlled authorization is crucial in
centrally stored DBMSs.
4. User views are derived database tables. A single table may contribute data to
several different views On the other hand, simple views may be constructed from a
single table.
5. Tables that are logically related in the data model need to be physically linked. The
degree of association between the tables (i.e., 1:1, 1:M, or M:M) determines how the
linking occurs. The key-assignment rules for linking tables are discussed below:
• Where a true 1:1 association exists between tables, either (or both) primary
keys may be embedded as foreign keys in the related table.
• Where a 1:M (or 1:0,M) association exists, the primary key of the 1 side is
embedded in the table of the M-side.
• To represent the M:M association between tables, a link table needs to be
created which has a combined (composite) key consisting of the primary keys of
two related tables.
6. The entity relationship (ER) diagram is the graphical representation technique used
to depict a data model. Each entity in a ER diagram is named in the singular noun
form, such as Customer rather than Customers. The labeled line connecting two
entities describes the nature of the association between them. This association is
represented with a verb, such as shipped, requests, or receives. The ER diagram
also represents cardinality (the degree of association between two entities). Four
basic forms of cardinality are possible: zero or one (0,1), one and only one (1,1),
zero or many (0,M), and one or many (1,M). These are combined to represent
logical associations between entities such as 1:1, 1:0,M, and M:M.
7. SQL allows users to retrieve data from many different files without the assistance of
programmer professionals. Thus, if the user has access to data files and knows
SQL, which is very user friendly, the user may retrieve the data instantaneously.
8. The data was not centrally stored for many different applications to use in the
traditional data management environment. Because it is centrally stored and shared
by many users in a database environment, the need arose for an individual to care
for and control these files. The database administrator is responsible for database
planning, developing the data requirements and data dictionary, database design
and controls, database implementation and access controls, operation and
maintenance, and establishing and reviewing the standards and procedures.
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9. The system programmer’s program should not have access to the data, except
perhaps temporarily to test the programs. The database administrator controls the
access to the data. If one person has the authority to both write programs and
access data, then control issues become a concern. The potential to commit fraud or
embezzlement or to destroy or alter the company’s records increases.
10. Neither table can donate an embedded key to the other, because both are on the
“many” side. The only solution, therefore, is to create a new link table containing the
key fields of both tables.
11. Tables that are not normalized contain anomalies which require excessive updates
to tables, prevent data from being stored properly, and may cause unintentional
deletion of data. Accountants need to be familiar with normalization issues, because
these anomalies threaten the integrity of the financial data of the organization.
12. A database lockout prevents multiple users from accessing the same table
simultaneously and making changes to data values while they are temporarily
inconsistent. Lockouts force changes to be made sequentially to ensure data accuracy.
13. Database concurrency controls ensure the completeness and accuracy of a
distributed database at remote sites where the same beginning data balances are
updated by different transactions. This is accomplished by serializing and timestamping
transactions. Depending on the need for data currency, the time-stamped
data will be reconciled and posted to all distributed databases.
14. Database accounting systems are transaction-based rather than account-based.
The focus is on capturing important details of transactions that may be lost when
they are forced into the structure of traditional accounting records. The transaction
tables are then to be used to reconstruct traditional accounting records, such as
Accounts Receivable and Accounts Payable.
15. Where a true 1:1 association exists between tables, either (or both) primary keys
may be embedded as foreign keys in the related table. On the other hand, when the
lower cardinality value is zero (1:0,1), a more efficient table structure can be
achieved by placing the 1-side (1:) table’s primary key in the zero-or-one (:0,1) table
as a foreign key. Assume that a company has 1000 employees, but only 100 of them
are sales staff. Also assume that each sales person is assigned a company car.
Therefore, every occurrence in the Employee entity is associated with either zero or
one occurrence in the Company Car entity. If we assigned the Company Car (:0,1)
side primary to the Employee (:1) table as a foreign key, then most of the foreign
keys will have null (blank) values. While this approach would work, it could cause
some technical problems during table searches. Correctly applying the keyassignment
rule solves this problem, because all Company Car records will have an
employee assigned, and no null values will occur.
16. The insertion and update anomalies would create record keeping and operational
problems for the firm. However, flawed databases design that prevents the insertion
of records, or requires the user to perform excessive updates, would attract attention
quickly. The presence of the deletion anomaly is less conspicuous, but potentially
more serious from an accounting perspective. Because the deletion anomaly may go
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undetected, the user may be unaware of the loss of important data until it is too late.
This anomaly can result in the unintentional loss of critical accounting records and
the destruction of the audit trail.
17. The organization’s business rules directly impact the structure of the database
tables. If the database is to function properly, its designers need to understand the
organization’s business rules, as well as the specific needs of individual users. For
example:
1. When an organization decides to purchase the same items of inventory from
different suppliers, the cardinality between the Supplier and Inventory tables is M:M.
2. When a the company purchases all items of a certain type from only one supplier,
the cardinality between Supplier and Inventory tables is 1:M respectively.
3. A policy that a separate receiving report is prepared for the receipt of goods specified
on a single purchase order will result in a 1:1 cardinality between the receiving report
and purchase order tables. If, however, multiple purchase orders are combined on a
single receiving report, then the cardinality between these tables will be 1: M
respectively.
18. The partitioned approach works best for organizations that require minimal data
sharing among users at remote sites. To the extent that remote users share
common data, the problems associated with the centralized approach will apply. The
primary user must now manage requests for data from other sites. Selecting the
optimum host location for the partitions, to minimize data access problems, requires
an in-depth analysis of end-user data needs.
19. To achieve data currency, simultaneous access to individual data elements or
records by multiple users needs to be prevented. The solution to this problem is a
database lockout, which is a software control that prevents multiple simultaneous
accesses to data. A deadlock occurs when multiple users seeking access to the
same set of records lockout each other. As a result, the transactions of all users
assume a “wait” state until the locks are removed. A deadlock is a permanent
condition that must be resolved by special software that analyzes each deadlock
condition to determine the best solution.
20. The primary justification for a replicated database is to support read-only queries in
situations involving a high degree of data sharing, but no primary user exists. With
data replicated at every site, data access for query purposes is ensured, and
lockouts and delays due to network traffic are minimized. A potential problem arises,
however, when replicated databases need to be updated by transactions. Since
each site processes only local transactions, the common data attributes that are
replicated at each site will be updated by different transactions and thus, at any point
in time, will have uniquely different values. System designers need to employ
currency control techniques to ensure that transactions processed at different
locations are accurately reflected in all the database copies.
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MULTIPLE CHOICES
1. D
2. C
3. D
4. E
5. D
6. D
7. A
8. C
9. B
10. C
11. D
12. C
13. D
14. C
15. A
16. D
17. A
18. D
PROBLEMS
1. August 23, 199X
MEMO TO: Al Brindifi, VP Operations
Carla Glasser, VP Finance
James Closter, VP Marketing
Julia Tinner, Controller
Beth Clark, Manager of Information Systems
FROM: Solutions Consultants
SUBJ: Conversion of data processing systems
After examining the operations of your organization and deriving a rough-cut estimate of
your needs, this consulting team feels that your organization would benefit greatly from
a database management system. A database management system will allow data to be
shared amongst the departments, thus facilitating communication. One of the problems
that has been brought repeatedly to our attention, is the need for information by user
groups, which is currently kept by the organization. These user groups are having
trouble gaining access to the data, because it does not reside in that user groups’
application. A database management system will provide a central data source,
whereby each authorized user group may gain access to the data it needs. Further, we
see many inefficiencies in processing data due to data duplication by various
applications. An even greater problem is that the data is oftentimes not consistent from
one application to another. The DBMS will reduce data duplication and data
redundancy. We propose that you begin a conversion to a DBMS. This conversion will
require that a database administrator be appointed or hired. A DBMS requires that the
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central data store be diligently planned, managed, and maintained. The database
administrator would perform these functions, as well as control user access to the data.
2. a. indexed sequential or indexed random; least optimal: sequential
b. indexed random or hashing; least optimal: sequential
c. sequential; least optimal: indexed random
d. sequential or pointer; least optimal: indexed random
e. indexed random or hashing; least optimal: sequential
f. indexed random or hashing; least optimal: sequential
g. indexed random; least optimal: hashing
3.
ER Diagram for Video Store
Copy DVD Supplier
Customer
Household
Member
Supplier Table
Supplier ID Supplier
(PK) Name
Supplier/DVD Table
Supplier ID DVD #
(PK) (PK)
DVD Table
DVD #
(PK)
Copy Table
Copy ID
(PK)
DVD
Name
DVD #
(FK)
Supplier
Address
DVD
Genre
Terms Balance Supplier
Phone #
Year of
Release
Cost
Rental
Time
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Customer Table
Customer Name of
Phone Primary
#(PK) Customer
Household Member Table
Member # Customer
(PK) Phone #
(FK)
Address
Name of
Household
Member
Credit
Card #
Age
Restrictions
4. Mail order catalogues are beginning to be customized based upon the preferences
and purchasing patterns of the customers. If data is stored regarding the customer
preferences and their buying patterns, then catalogues containing only the items
which are believed to be of value to the customer may be contained in the
catalogue. Printing costs and postage costs would be saved. Also, more items could
be included which fit the pattern of the customer. Further, the customer does not
have to weed through the catalogue to find the items that he or she likes. The
technology is changing such that customized or semi-customized (for groups of
people) catalogues are a reality.
Listed below are some files and some fields in the files which would be necessary in
addition to the traditional accounts receivable, cash receipts, vendor, and general ledger
files.
Customer Sales Inventory Inventory Type
Master File File Master File File
Customer Number Customer Number Item Number Product Type
Name
Sales Order Number Item Description Product Classification
Address $ Amount of Items Product Type
Phone Taxes Quantity on Hand
Credit Card Type Freight Selling Price
Credit Card Number
Total Amount
Credit Card Expiration
Last Purchase Date
Cumulative Purchase Amount
Purchases in Last 12 months Sales Order Detail
Purchases in Last 3 months File
$ Purchases of Type A Sales Order Number
$ Purchases of Type B Item Number
$ Purchases of Type C Quantity
$ Purchases of Type D Discount
Request Type A catalogue
Request Type B catalogue
Request Type C catalogue
Request Type D catalogue
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5. Lockout. The example below illustrates how two different transactions are being
processed against the same AR control account within the same time frame. The
individual logic steps are shown in their actual sequence of execution. If no database
lockout were in place, the AR Control value of 20,000 is retrieved by both users of
the system. One user is posting a payment to Sub Account 1 of $500 and the other
is posting a payment to Sub Account 2 for $800.
AR
Control
Time IPU Instruction Sub Acct 1 Sub Account 2 Account
1:00:001 A Read sub acct 1 1,000
1:00:001 B Read sub acct 2 3,000
1:00:002 A Update sub acct 1 500
1:00:002 B Update sub acct 2 2,200
1:00:003 A Read control acct 20,000
1:00:003 B Read control acct 20,000
1:00:004 A Update control acct 19,500
1:00:005 B Update control acct 19,200
The update process does not reflect the second to last instruction executed. The AP
Control Account should reflect payments received of $1,300, but it only $800 of
payments are accounted for. Thus, a transaction is lost, and the control and subsidiary
ledgers are out of balance.
Deadlock. A deadlock occurs when multiple sites lock out each other. Take for
example, a mail order company in which two customers are processing transactions
simultaneously. Customer 1 wants to order 2 items—Item A and Item B. Customer 2 is
purchasing Item B and Item A. Customer 1 informs the phone clerk that he or she
wants Item A, and the record for Item A is locked until the order is complete. Meanwhile,
Customer 2 orders Item B from another phone clerk who locks it. Customer 1 then
requests Item B, which is locked by Customer 2’s order. The phone clerk apologizes for
the delay and says the system is slow today. Customer 2 then requests Item A, which is
locked by Customer 1’s order. The phone clerk helping Customer 2 apologizes for the
delay and says the system is slow today. Unfortunately, neither transaction can be
completed, resulting in deadlock. This condition will not be resolved unless some type of
intervention occurs.
6. SELECT Customer Name, Inventory Number, Item Description, Due Date
FROM Customer Table, Rental Line Items Table
WHERE Due Date < Today
7. The best distributed approach is a replicated database.
Reasoning
• The users are distributed around the country and need rapid access to data. A
centralized model may result in long delays because of network traffic and
database lockout.
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• User data needs are common not unique. Since there are no identifiable primary
users, partitioning the database will accomplish nothing.
• Because usage is read-only, changes will not occur and database concurrency is
not a problem.
8. The best distributed approach is a partitioned database.
Reasoning
• The users are distributed around the country and need rapid access to data. A
centralized model may result in long delays because of network traffic and
database lockout.
• User data needs are unique with identifiable primary users. There is no need to
replicate the entire database.
• Since users are unique, changes to the database will not cause database
concurrency problem.
9. The first step is to remove repeating groups. The removal of repeating groups
results in the following two tables. Due Date has been removed because it is a
calculated field. Student ID Number is the primary key for the Student table. Student
Id Number and Book Call No. together are the primary key for the Library table.
Student table is now in 3NF. Library table requires further normalization.
Student Table
Student ID
Number
Library Table
Student ID
Number
Student First
Name
Student Last
Name
No. of Books
Out
Book Call No. Book Title Date Out
The second step is to remove partial dependencies from Library table.
Book Title is partially dependent on the Book Call No. component of the primary key.
This assumes that the call number is unique to the book, and not to the event of
borrowing the book. It also assumes that more than one copy of the book may exist in
the library and that all copies have the same call number. Removing the partial
dependency results in the tables below:
Transaction Table
Student ID
Number
Book Table
Book Call No.
Date Out
Book Call No.
Book Title
Book Call No. is the primary key for the new table Book. Since no transitive
dependencies exist, all three tables (Student, Transaction, and Book) are now in 3NF.
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10. Table Textbook
ISBN # Title
(PK)
Publisher
(FK)
Table Publisher
Publisher
(PK)
Address Phone #
Table Class
Course #
(PK)
Course
Name
Table Semester
Term Year
#(PK)
Professor
(FK)
Semester
Cost
Selling
Price
Quantity
on Hand
Days Room # Term #
(FK)
Table Professor
Employee
# (PK)
Name Address Phone Title
11. See diagram below.
PK Inventory Table FK
Part # Description QOH Reorder Point EOQ Unit Cost Vendor #
PK
12. See diagram below.
Vendor # Vendor Name Vendor
Address
PK
Part # Description QOH Reorder
Point
Telephone Vendor Table
EOQ Inventory Table
Part # Vendor # Unit cost
Vendor # Vendor Name Vendor Address Telephone
Note: This is an example of a many-to-many relation between the inventory and vendor tables.
The solution requires a link table, which also contains Unit Cost data. A composite key of
Part # and Vendor # is needed to define the Unit Cost attribute, because there are many
prices for each item carried, depending on which vendor supplies the part.
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13. See diagram below.
Customer #
Customer
Name
Address
* Customer
Total
Customer
Table
Invoice # Date *Invoice Total Customer # Invoice Table
Invoice # Part # Quantity
*Extended
Price
Line Item Table
Part
Number
Unit
Price
Inventory Table
* Could be a calculated field
14. Table Employee
Employee #
(PK)
Name Address Date Hired Exemptions Marital
Status
Table PO
PO # (PK) Date Employee # Vendor # (FK)
(FK)
Table PO/Item
PO # (PK)
Item # (PK) Quantity
Table Item
Item # (PK) Description On Hand Cost Price Location
Table Vendor
Vendor # (PK) Name Address Contact Terms Balance
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15.
Solution to Problem 9-15
Customer
Table
(PK) Customer Num
Salesman
Table
(PK) Salesman Num
None
None
Cash
Receipts
Table
1 1 1
Sales Order
Table
M M M
Inventory
Table
(PK) Cash Rec Num
Customer Num (FK)
(PK) Invoice Num
Customer Num (FK)
Salesman Num (FK)
Part Number (FK)
M 1
(PK) Part Number
None
M
Supplier
Table
Link
Table
(PK) Vendor Num
None
M
(PK) Part Number
(PK) Vendor Num
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16. a. and b.
Rejected Entities
Payroll Clerk
Reason
Violates rule 1 and 2––Wording suggests only
one clerk (rule 1) and no evidence of attributes
unique to this entity (rule 2)
Violates Rule 1––The company is a single
occurrence
Sagerod Manufacturing
Company
Cash Disbursements Clerk Violates rule 1 and 2
Time Clock Machine Violates rule 1 and 2
Supervisor Violates rule 1 and 2
Check for the Total Payroll This is a view––Violates rule 2
Paycheck This is a view––Violates rule 2
Payroll Register This is a view––Violates rule 2
Valid Entities
Employee
Paycheck Register
Cash Disbursement Journal
Time Card
Earnings Record
Problem 16, part c
Data Model of Payroll System
Employee
Submits
Time Card
Receives
Contains
Paycheck
Register
Derived from
Earnings
Record
Contains
Cash
Disbursement
Journal
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17. a. and b.
Rejected Entities
Accounts Payable
Department Clerk
Safe Buy Grocery
Stores
Receiving Report
Summary
Part-Time Employees
Unloading Personnel
Sales
Representatives
Obsolescence
Reports
Invoice (physical)
Check (physical)
Payment Summary
Purchase Requisition
Customers
Reason
Violates rule 1 and 2––Wording suggests only one
clerk (rule 1) and no evidence of attributes unique to
this entity (rule 2)
Violates Rule 1––The company is a single
occurrence
This is a view––It derives entirely from receiving
report and thus violates rule 2
Violates rule 2––Assumption: no employee specific
data need to be captured by this system
Violates rule 2––Assumption: no employee specific
data need to be captured by this system
Violates rule 2––Assumption: The company does not
capture Sales Rep data unique to each transaction.
This is a view––Derived from inventory records
Violates rule 2
This is a view––Used to create Invoice Record
Violates rule 2
This is a view––Derived from Check register
records. Violates rule 2
This is a view––Derived from Check register records
Violates rule 2
This is a view––Used to create Purchase Order
Violates rule 2
Not relevant to this system
Valid Entities
Purchase Manager
Reason
Assumption: all store purchase managers will use
the system. This entity will consist of multiple
occurrences and provide manager/store-specific
data not contained in other entities.
Supplier Meets conditions of Rules 1 and 2
Inventory Meets conditions of Rules 1 and 2
Purchase Order Meets conditions of Rules 1 and 2
Receiving Report Meets conditions of Rules 1 and 2
Invoice (record) Meets conditions of Rules 1 and 2
Payment Obligation Meets conditions of Rules 1 and 2
Check (register) Meets conditions of Rules 1 and 2
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Problem 9-17, part c – Data Model of Purchases Procedures
Updates
Inventory
Contains
Supplies
Supplier
Submits
Sent To
Receives
Supplier Invoice
Check
Establishes
Initiates
Payment
Obligation
Pertains
To
Is Associated With
Is
Associated
With
Receiving Report
Is Associated With
Purchase Order
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Updates
Inventory
Part Number
Description
Quantity on Hand
Reorder Point
Unit Cost
Contains
Contains
Pertains To
Inven/Supplier Link
Part Number
Supplier Number
PO Item Detail
Item Number
PO Number
Order Quantity
Rec Rept Detail
Part Number
Rec Rept Number
Quantity Received
Condition
Supplier
Supplier Number
Supplier Name
Supplier Address
Supplier Tel Number
Submits
Sent To
Receives
Check
Check Number
Supplier Number [FK]
Amount
Payment Date
Supplier Invoice
Invoice Number
Supplier Number
PO Number [FK]
Date
Amount
Contains
Contains
Initiates
Payment Obligation
Cash Disb Num
Check Number [FK]
Supplier Number [FK]
PO Number [FK]
Invoice Number [FK]
Payment Due Date
Amount
Establishes
Pertains
To
Receiving Report
Rec Rept Number
PO Number [FK]
Date Received
Carrier Code
Bill of Lading Number
Prepaid
Collect
Is Associated With
Is Associated With
Is Associated With
Purchase Order
PO Number
Supplier Number
Date of Purchase
Requested Delivery Date
© 2008 Cengage Learning

Chapter 9 Page 358
18. Solution a. and b.
Rejected Entities
Accounts Payable
Department Clerk
Safe Buy Grocery
Stores
FA Receiving Report
Summary
Receiving Clerk
Accounts Payable
Manager
Depreciation
Schedule
Invoice (physical)
Check (physical)
Payment Summary
Purchase Requisition
Store Manager
Reason
Violates rule 1 and 2—Wording suggests only one
clerk (rule 1) and no evidence of attributes unique to
this entity (rule 2)
Violates Rule 1—the company is a single occurrence
This is a view—It derives entirely from receiving
report and thus violates rule 2
Violates rule 2—Assumption: no employee specific
data need to be captured by this system
Violates rule 2—Assumption: no employee specific
data need to be captured by this system
Assumption: This is a view—Derived from data in
inventory records Violates rule 2
This is a view—Used to create Invoice Record
Violates rule 2
This is a view—Derived from Check register records.
Violates rule 2
This is a view—Derived from Check register records.
Violates rule 2
This is a view—Used to create Purchase Order.
Violates rule 2
Assumption: manager/store-specific data will be
contained in other entities i.e. Purchase Order
Valid Entities Reason
Supplier Meets conditions of Rules 1 and 2
Fixed Assets Inventory Meets conditions of Rules 1 and 2
Purchase Order Meets conditions of Rules 1 and 2
Receiving Report Meets conditions of Rules 1 and 2
Invoice (record) Meets conditions of Rules 1 and 2
Payment Obligation Meets conditions of Rules 1 and 2
Check (register) Meets conditions of Rules 1 and 2
© 2008 Cengage Learning

Chapter 9 Page 359
Updates
Fixed
Asset
Inventory
Contains
Supplies
Supplier
Submits
Sent To
Receives
Supplier Invoice
Check
Establishes
Initiates
Payment
Obligation
Pertains To
Is Associated With
Is
Associated
With
Receiving Report
Purchase Order
© 2008 Cengage Learning

Chapter 9 Page 360
FA Inventory
Part Number
Updates
Description
Quantity on
Location
Cost
Accumulated Depr
Depreciation method
Contains
Contains
Pertains To
Inven/Supplier Link
Part Number
Supplier Number
PO Item Detail
Part Number
PO Number
Order Quantity
Rec Rept Detail
Supplier
Sent To
Part Number
Rec Rept Number
Quantity Received
Condition
Supplier Number
Supplier Name
Supplier Address
Supplier Tel Number
Submits
Check
Check Number
Supplier Number [FK]
Amount
Payment Date
Receives
Supplier Invoice
Invoice Number
Supplier Number
PO Number [FK]
Date
Amount
Contains
Contains
Initiates
Payment
Cash Disb Num
Check Number [FK]
Supplier Number [FK]
PO Number [FK]
Invoice Number [FK]
Payment Due Date
Amount
Establishes
Pertains To
Receiving Report
Rec Rept Number
PO Number [FK]
Date Received
Carrier Code
Bill of Lading Number
Prepaid
Collect
Is Associated With
Is Associated With
Is Associated
With
Purchase Order
PO Number
Supplier Number
Date of Purchase
Requested Delivery Date
© 2008 Cengage Learning

Chapter 9 Page 361
19.
a.
Customer
Sales Order
b.
Item
Purchase Order
c.
Automobile
Sales Order
d.
Item
Customer
e.
Customer
Movie
20. Solution: a. and b.
Rejected Entities
Sales Representative
D&F Music Club
John, Billing Clerk
Chris, Warehouse
Clerk
Sandy, AR Clerk
Scott, Mailroom Clerk
Customer Invoice
(physical)
Customer Check
(physical)
Reason
Assumption: Sales representative specific data will
be contained in customer record. Violates rule 2
Violates Rule 1—the company is a single
occurrence
Violates rule 2—Assumption: no employee specific
data need to be captured by this system
Violates rule 2—Assumption: no employee specific
data need to be captured by this system
Violates rule 2—Assumption: no employee specific
data need to be captured by this system
Violates rule 2—Assumption: no employee specific
data need to be captured by this system
This is a view—created from Customer Invoice
record. Violates rule 2
This is a view—Derived from Check register
records. Violates rule 2
© 2008 Cengage Learning

Chapter 9 Page 362
Rejected Entities
Remittance Advise
Remittance List
Laura, Cash Receipts
Clerk
Deposit Slip
Warehouse Manager
Demand Forecast
Purchase Requisition
Sara, Purchasing
Clerk
PO Blind Copy
Cash Disbursement
Clerk
Payment Check
(Physical)
Packing Slip
Reason
This is a view—Derived from Customer Invoice
record at time of billing. Violates rule 2
This is a view—Used to create Cash Receipt
record. Violates rule 2
Violates rule 2—Assumption: no employee specific
data need to be captured by this system.
This is a view—Created from Cash Receipt record.
Violates rule 2
Violates rule 2—Assumption: no employee specific
data need to be captured by this system.
View derived from marketing system
Assumption: This is a View derived from Inventory
records.
Violates rule 2—Assumption: no employee specific
data need to be captured by this system.
This is a view—derived from Purchase Order
record. Violates rule 2
Violates rule 2—Assumption: no employee specific
data need to be captured by this system.
This is a view—Created from Check Register
record. Violates rule 2
This is a view—Created from Sales Order record.
Violates rule 2
Valid entities
Reason
Customer Meets conditions of Rules 1 and 2
Sales Order Meets conditions of Rules 1 and 2
Sales Journal Meets conditions of Rules 1 and 2
Inventory Sub Ledger Meets conditions of Rules 1 and 2
Bill of Lading Meets conditions of Rules 1 and 2
General Ledger Meets conditions of Rules 1 and 2
Cash Receipts Journal Meets conditions of Rules 1 and 2
Return Record Meets conditions of Rules 1 and 2
Purchase Order Meets conditions of Rules 1 and 2
Supplier Meets conditions of Rules 1 and 2
Account Payable Meets conditions of Rules 1 and 2
Receiving Report Meets conditions of Rules 1 and 2
Supplier Invoice (record) Meets conditions of Rules 1 and 2
Check (register) Meets conditions of Rules 1 and 2
© 2008 Cengage Learning

Chapter 9 Page 363
Updates
Inventory
Sub
Ledger
Contains
General Ledger
Supplies
Supplier
Submits
Sent To
Receives
Supplier Invoice
Check Register
Establishes
Initiates
Accounts Payable
Pertains
To
Is Associated With
Is
Associated
With
Receiving Report
Purchase Order
Is Associated With
© 2008 Cengage Learning

Chapter 9 Page 364
Places
Pertains To
Customer
Sales Order
Is
Associated
With
Inventory Sub Ledger
Sends
Sales
Journal
Sends
Relates
To
Cash Receipt
(Journal)
Bill of Lading
General Ledger
Pertains To
Relates To
Sales Return
Relates To
© 2008 Cengage Learning

Chapter 9 Page 365
Updates
Is Associated
With
General Ledger
GL Account
Number
Acct Desc.
Acct Class
Beginning Bal
Total Dr
Total Cr
Current Bal
Inventory
Part Number
GL Account Number [FK]
Description
Quantity on Hand
Reorder Point
Unit Cost
Contains
Supplier
Supplier Number
Supplier Name
Supplier Add.
Supplier Tel Number
Contains
Submits
Pertains To
Inven/Supplier Link
Part Number
Supplier Number
Sent To
PO Item Detail
Item Number
PO Number
Order Quantity
Rec Rept Detail
Part Number
Rec Rept Number
Quantity
Received
Condition
Is
Associated
With
Check
Check Number
GL Account Number [FK]
Supplier Number [FK]
Amount
Payment Date
Receives
Supplier Invoice
Invoice Number
Supplier Number
PO Number [FK]
Date
Amount
Establishes
Contains
Contains
Initiates
Accounts Payable
Cash Disb Num
Check Number [FK]
GL Account Num [FK]
Supplier Num [FK]
PO Number [FK]
Invoice Num [FK]
Payment Due Date
Amount
Pertains
To
Receiving Report
Rec Rept Number
PO Number [FK]
Date Received
Carrier Code
Bill of Lading
Number
Prepaid
Collect
Is Associated With
Is Associated With
Is Associated With
Purchase Order
PO Number
Supplier Number [FK]
Date of Purchase
Requested Delivery Date
© 2008 Cengage Learning

Chapter 9 Page 366
Sends
Customer
Cust Acct Num
Name
Address
Tel num
E-Mail Address
Credit limit
Available Credit
Current Balance
Last Payment Date
Sends
Cash Receipt
(Journal)
Customer Check Num
Customer Account
Num
GL Account Number
[FK]
Amount
Date
Places
Is
Associated
With
Sales Journal
Sale Trans Num
Sales Order Num [FK]
GL Account Number [FK]
Amount
Date
Relates
To
Sales Order
Sales Order Num
BOL Num [FK]
Cust Acct Num [FK]
Order Date
Ship Date
Terms
Contains
Sales Order
Details
Part Number
Sales Order Num
Quantity
Pertains
To
Inventory Sub
Ledger
Part Number
GL Account Number
[FK]
Description
Quantity on Hand
Reorder Point
Unit Cost
Sales Return
Relates To
General Ledger
GL Account Number
Acct Description
Acct Class
Beginning Bal
Total Dr
Total Cr
Current Bal
Pertains To
Bill of Lading
BOL Num
Date
Carrier Code
Sale Return Num
Relates To
Cust Acct Num [FK]
GL Account Number
[FK]
Part Num
Amount
Condition
Date
© 2008 Cengage Learning

Chapter 9 Page 367
Customer
Carrier
Approve
Customer
Returns
Take
Customer
Order
Sales Order
Verify and
Pick Goods
BOL
Open Mail
Prepare
Remit List
Sales Journal
Prepare
Invoice &
Record Sale
Return Copy
Order Data
Invoice
Packing Slip
and BOL
Return Authorization
Number
Request
Return
Sales Return
Inventory
Sub Ledger
Return Copy
Remittance Advice & Check
Customer Data
Sales Data
Remittance List and Checks
Bank
Customer
Record
Update
Customer
and
GL Accounts
Deposit
Slip
Update
Accounts
Deposit
Checks
Deposit
Slip
General
Ledger
Cash Rec
Journal
Cash Rec
Data
© 2008 Cengage Learning

Chapter 9 Page 368
Market
Research
Demand Forecast
Supplier
Review
Records
Inventory Sub
Ledger
Goods and
Supporting
Docs
Purchase Req
Supplier
Select
Supplier
and
Create PO
Purchase
Order
Blind Cpy
Receive
Counts
Inspects
Check
Register
Purchase Order
Supplier
Invoice
Purchase
Order
Reconcile
and Update
Accounts
Receiving
Report
Accts Payable
General
Ledger
Make
Payment on
Due Date
Check
Supplier
Invoice
© 2008 Cengage Learning