Database System

© 2006 Prentice Hall Business Publishing Accounting Information Systems, 10/e Romney/Steinbart 1 of 95
DATA BASE SYSTEM
Pemrosesan data berbasis File vs
Berbasis Database

FILE VS. DATABASES
• Let’s examine some basic principles about how data are
stored in computer systems.
– An entity is anything about which the organization wishes to
store data. At your college or university, one entity would be the
student.
STUDENTS
Student ID Last Name First Name
Phone
Number Birth Date
333-33-3333 Simpson Alice 333-3333 10/11/84
111-11-1111 Sanders Ned 444-4444 11/24/86
123-45-6789 Moore Artie 555-5555 04/20/85

FILE VS. DATABASES
– Information about the attributes of an entity (e.g., the
student’s ID number and birth date) are stored in
fields.
STUDENTS
Phone
Number Birth Date
333-33-3333 Simpson Alice 333-3333 10/11/84
111-11-1111 Sanders Ned 444-4444 11/24/86
123-45-6789 Moore Artie 555-5555 04/20/85

FILE VS. DATABASES
– All the fields containing data about one entity (e.g.,
one student) form a record.
– The example below shows the record for Artie Moore.
STUDENTS
Phone
Number Birth Date
333-33-3333 Simpson Alice 333-3333 10/11/84
111-11-1111 Sanders Ned 444-4444 11/24/86
123-45-6789 Moore Artie 555-5555 04/20/85

FILE VS. DATABASES
– A set of all related records forms a file (e.g., the
student file).
– If this university only had three students and five fields
for each student, then the entire file would be
depicted below.
STUDENTS
Phone
Number Birth Date
333-33-3333 Simpson Alice 333-3333 10/11/84
111-11-1111 Sanders Ned 444-4444 11/24/86
123-45-6789 Moore Artie 555-5555 04/20/85

FILE VS. DATABASES
– A set of interrelated, centrally coordinated files forms
a database.
Student
File
Class
File
Advisor
File

FILE VS. DATABASES
• This proliferation of master
files created problems:
– Often the same information was
stored in multiple master files.
– Made it more difficult to
effectively integrate data and
obtain an organization-wide view
of the data.
– Also, the same information may
not have been consistent
between files.
• If a student changed his
phone number, it may have
been updated in one master
file but not another.
Master File 1
Fact A
Fact B
Fact C
Master File 2
Fact A
Fact D
Fact F
Master File 1
Fact A
Fact B
Fact F
Enrollment
Program
Fin. Aid
Program
Grades
Program

FILE VS. DATABASES
• A database is a set
of inter-related,
centrally
coordinated files.
Database
Fact A Fact B
Fact C Fact D
Fact E Fact F
Enrollment
Program
Fin. Aid
Program
Grades
Program
Database
Management
System

FILE VS. DATABASES
• The database approach
treats data as an
organizational resource
that should be used by
and managed for the
entire organization, not
just a particular
department.
• A database management
system (DBMS) serves
as the interface between
the database and the
various application
programs.
Database
Fact A Fact B
Fact C Fact D
Fact E Fact F
Enrollment
Program
Fin. Aid
Program
Grades
Program
Database
Management
System

FILE VS. DATABASES
• The combination of
the database, the
DBMS, and the
application
programs that
access the
database is
referred to as the
database system.
Database
Fact A Fact B
Fact C Fact D
Fact E Fact F
Enrollment
Program
Fin. Aid
Program
Grades
Program
Database
Management
System

FILE VS. DATABASES
• The person
responsible for the
database is the
database
administrator.
• As technology
improves, many large
companies are
developing very large
databases called data
warehouses.
Database
Fact A Fact B
Fact C Fact D
Fact E Fact F
Enrollment
Program
Fin. Aid
Program
Grades
Program
Database
Management
System

IMPORTANCE AND ADVANTAGES OF
DATABASE SYSTEMS
• As accountants, you are likely to audit or work
for companies that use database technology to
store, process, and report accounting
transactions.
– Many accountants work directly with databases and
will enter, process, and query databases.
– Some will develop and evaluate internal controls
necessary to ensure database integrity.
– Others will be involved in the design and
management of databases.

DATABASE SYSTEMS
• Database technology provides the
following benefits to organizations:
– Data integration • Achieved by combining
master files into larger
pools of data accessible
by many programs.

DATABASE SYSTEMS
– Data integration
– Data sharing • It’s easier to share data
that’s integrated.

DATABASE SYSTEMS
– Data sharing
– Reporting flexibility
• Reports can be revised easily and
generated as needed.
• The database can easily be browsed to
research problems or obtain detailed
information.

DATABASE SYSTEMS
– Data sharing
– Minimal data redundancy and
inconsistencies • Because data items are
usually stored only once.

DATABASE SYSTEMS
– Data sharing
– Minimal data redundancy and inconsistencies
– Data independence
• Data items are independent of the programs that
use them.
• Consequently, a data item can be changed
without changing the program and vice versa.
• Makes programming easier and simplifies data
management.

DATABASE SYSTEMS
– Data sharing
– Central management of data
• Data management is more efficient
because the database administrator is
responsible for coordinating, controlling,
and managing data.

DATABASE SYSTEMS
– Data sharing
– Central management of data
– Cross-functional analysis
• Relationships can be explicitly defined and
used in the preparation of management
reports.
• EXAMPLE: Relationship between selling
costs and promotional campaigns.

DATABASE SYSTEMS
• Logical and Physical Views of Data
– In file-oriented systems, programmers must
know the physical location and layout of
records used by a program.
• They must reference the location, length, and
format of every field they utilize.
• When data is used from several files, this process
becomes more complex.

DATABASE SYSTEMS
• Database systems overcome this problem
by separating the storage and use of data
elements.
– Two separate views of the data are provided:
• Logical view
• How the user or programmer conceptually
organizes and understands the data.

DATABASE SYSTEMS
elements.
• Logical view
• Physical view
• How and where the data are physically
arranged and stored.

DATABASE SYSTEMS
elements.
• Logical view
• Physical view
– Separating these views facilitates
application development, because
programmers can focus on coding the
logic and not be concerned with storage
details.

Scholarship Distribution
Fr.
5%
Soph.
24%
Jr.
38%
Sr.
33%
Database
Enrollment by Class
Logical View—User A Logical View—User B
DBMS
Operating
System
The DBMS translates
users’ logical views
into instructions as to
which data should be
retrieved from the
database.

Scholarship Distribution
Fr.
5%
Soph.
24%
Jr.
38%
Sr.
33%
Database
Enrollment by Class
Logical View—User A Logical View—User B
DBMS
Operating
System
The operating system
translates DBMS
requests into
instructions to
physically retrieve
data from various
disks.

DATABASE SYSTEMS
• The DBMS handles the link between the
physical and logical views of the data.
– Allows the user to access, query, and update
data without reference to how or where it is
physically stored.
– The user only needs to define the logical data
requirements.

DATABASE SYSTEMS
• Separating the logical and physical views of data
also means users can change their
conceptualizations of the data relationships
without making changes in the physical storage.
• The database administrator can also change the
physical storage of the data without affecting
users or application programs.

DATABASE SYSTEMS
• Schemas
– A schema describes the logical structure of a
database.
– There are three levels of schema.
• Conceptual level
• The organization-wide view of the entire
database—i.e., the big picture.
• Lists all data elements and the relationships
between them.

Subschema--User A
Smith . . . A
Jones . . . B
Arnold . . .D
Subschema--User B Subschema--User C
Enroll
Cash
Receipt
Classes Student
Student Record Class Record
Student No. --character [9] Class Name --character [9]
Student Name --character [26] Dept No. --integer [4], non-null, index=itemx
SAT Score --integer [2], non-null, index=itemx Course No. --integer [4], non-null, index=itemx
Mapping external-level views to conceptual-level schema
Mapping conceptual-level items to internal-level descriptions

DATABASE SYSTEMS
• Schemas
database.
• External level
• A set of individual user views of portions of
the database, i.e., how each user sees the
portion of the system with which he
interacts.
• These individual views are referred to as
subschema.

Subschema--User A
Smith . . . A
Jones . . . B
Arnold . . .D
Enroll
Cash
Receipt
Classes Student

DATABASE SYSTEMS
• Schemas
database.
• External level
• Internal level
• A low-level view of the database.
• It describes how the data are actually
stored and accessed including:
– Record layouts
– Definitions
– Addresses
– Indexes

Subschema--User A
Smith . . . A
Jones . . . B
Arnold . . .D
Enroll
Cash
Receipt
Classes Student

Subschema--User A
Smith . . . A
Jones . . . B
Arnold . . .D
Enroll
Cash
Receipt
Classes Student
The
bidirectional
arrows
represent
mappings
between the
schema.

DATABASE SYSTEMS
• The DBMS uses the mappings to translate
a request by a user or program for data
(expressed in logical names and
relationships) into the indexes and
addresses needed to physically access
the data.

DATABASE SYSTEMS
• Accountants are frequently involved in
developing conceptual- and external-level
schema.
• An employee’s access to data should be
limited to the subschema of data that is
relevant to the performance of his job.

DATABASE SYSTEMS
• The Data Dictionary
– A key component of a DBMS is the data
dictionary.
• Contains information about the structure of the
database.
• For each data element, there is a corresponding
record in the data dictionary describing that
element.

DATABASE SYSTEMS
• Information provided for each element includes:
– A description or explanation of the element.
– The records in which it is contained.
– Its source.
– The length and type of the field in which it is stored.
– The programs in which it is used.
– The outputs in which it is contained.
– The authorized users of the element.
– Other names for the element.

DATABASE SYSTEMS
• Accountants should participate in the
development of the data dictionary because they
have a good understanding of the data elements
in a business organization, as well as where
those elements originate and how they are used.

DATABASE SYSTEMS
• The DBMS usually maintains the data dictionary.
– It is often one of the first applications of a newly
implemented database system.
– Inputs to the dictionary include:
• Records of new or deleted data elements.
• Changes in names, descriptions, or uses of existing
elements.
– Outputs include:
• Reports that are useful to programmers, database designers,
and IS users in:
– Designing and implementing the system.
– Documenting the system.
– Creating an audit trail.

DATABASE SYSTEMS
• DBMS Languages
–Every DBMS must provide a means of
performing the three basic functions of:
• Creating a database
• Changing a database
• Querying a database

DATABASE SYSTEMS
• DBMS Languages

DATABASE SYSTEMS
• Creating a database:
– The set of commands used to create the
database is known as data definition
language (DDL). DDL is used to:
• Build the data dictionary
• Initialize or create the database
• Describe the logical views for each individual user
or programmer
• Specify any limitations or constraints on security
imposed on database records or fields

DATABASE SYSTEMS
• DBMS Languages

DATABASE SYSTEMS
– The set of commands used to change the
database is known as data manipulation
language (DML). DML is used for
maintaining the data including:
• Updating data
• Inserting data
• Deleting portions of the database

DATABASE SYSTEMS
• DBMS Languages

DATABASE SYSTEMS
• Querying a database:
– The set of commands used to query the database is
known as data query language (DQL). DQL is used
to interrogate the database, including:
• Retrieving records
• Sorting records
• Ordering records
• Presenting subsets of the database
– The DQL usually contains easy-to-use, powerful
commands that enable users to satisfy their own
information needs.

DATABASE SYSTEMS
• Report Writer
– Many DBMS packages also include a report writer, a
language that simplifies the creation of reports.
– Users typically specify:
• What elements they want printed
• How the report should be formatted
– The report writer then:
• Searches the database
• Extracts specified data
• Prints them out according to specified format

DATABASE SYSTEMS
• Users typically have access to both DQL and
report writer.
• Access to DQL and DML are typically restricted
to employees with administrative and
programming responsibilities.

RELATIONAL DATABASES
• A DBMS is characterized by the type of
logical data model on which it is based.
– A data model is an abstract representation of
the contents of a database.
– Most new DBMSs are called relational
databases because they use the relational
model developed by E.F. Codd in 1970.

• The relational data model represents
everything in the database as being stored
in the forms of tables (aka, relations).

Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
Course ID Course Section Day Time
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
Relation
SCID Student ID Course
333333333-1234 333-33-3333 1234
333333333-1236 333-33-3333 1236
111111111-1235 111-11-1111 1235
111111111-1236 111-11-1111 1235
STUDENT x COURSE

• This model only describes how the data
appear in the conceptual- and external-
level schemas.
• The data are physically stored according
to the description in the internal-level
schema.

Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236
Each row is
called a tuple,
which rhymes
with “couple.”

Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
Each row
contains data
about a specific
occurrence of
the type of entity
in the table.
STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236

Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
Each column in
a table contains
information
about a specific
attribute of the
entity.
STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236

Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
A primary key is the
attribute or combination
of attributes that
uniquely identifies a
specific row in a table.
STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236

STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236
Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
In some tables, two or more attributes
may be joined to form the primary key.

ADVISORS
Advisor No. Last Name First Name Office No.
1418 Howard Glen 420
1419 Melton Amy 316
1503 Zhang Xi 202
1506 Radowski J.D. 203
STUDENTS
Student ID Last Name First Name Phone No.
Advisor
No.
333-33-3333 Simpson Alice 333-3333 1418
111-11-1111 Sanders Ned 444-4444 1418
123-45-6789 Moore Artie 555-5555 1503
A foreign key is an attribute in one table that is a primary key in
another table.

ADVISORS
1419 Melton Amy 316
1503 Zhang Xi 202
Foreign keys are used to link tables together.
STUDENTS
Advisor
No.
333-33-3333 Simpson Alice 333-3333 1418
111-11-1111 Sanders Ned 444-4444 1418
123-45-6789 Moore Artie 555-5555 1503

ADVISORS
1419 Melton Amy 316
1503 Zhang Xi 202
Other non-key attributes in each table store important
information about the entity.
STUDENTS
Advisor
No.
333-33-3333 Simpson Alice 333-3333 1418
111-11-1111 Sanders Ned 444-4444 1418
123-45-6789 Moore Artie 555-5555 1503

• Alternatives for Storing Data
– One possible alternate approach would be to
store all data in one uniform table.
– For example, instead of separate tables for
students and classes, we could store all data
in one table and have a separate line for each
student x class combination.

Student ID
Last
Name
First
Name Phone No. Course No.
Sectio
n Day Time
333-33-3333 Simpson Alice 333-3333 ACCT-3603 1 M 9:00 AM
333-33-3333 Simpson Alice 333-3333 FIN-3213 3 Th 11:00 AM
333-33-3333 Simpson Alice 333-3333 MGMT-3021 11 TH 12:00 PM
111-11-1111 Sanders Ned 444-4444 ACCT-3433 2 T 10:00 AM
111-11-1111 Sanders Ned 444-4444 MGMT-3021 5 W 8:00 AM
111-11-1111 Sanders Ned 444-4444 ANSI-1422 7 F 9:00 AM
123-45-6789 Moore Artie 555-5555 ACCT-3433 2 T 10:00 AM
123-45-6789 Moore Artie 555-5555 FIN-3213 3 Th 11:00 AM
• Using the suggested approach, a student taking three classes
would need three rows in the table.
• In the above, simplified example, a number of problems arise.

Student ID
Last
Name
First
Name Phone No. Course No. Sect. Day Time
• Suppose Alice Simpson changes her phone number. You need to
make the change in three places. If you fail to change it in all three
places or change it incorrectly in one place, then the records for
Alice will be inconsistent.
• This problem is referred to as an update anomaly.

Student ID
Last
Name
First
• What happens if you have a new student to add, but he hasn’t
signed up for any courses yet?
• Or what if there is a new class to add, but there are no students
enrolled in it yet? In either case, the record will be partially blank.
• This problem is referred to as an insert anomaly.

Student ID
Last
Name
First
• If Ned withdraws from all his classes and you eliminate all three of
his rows from the table, then you will no longer have a record of
Ned. If Ned is planning to take classes next semester, then you
probably didn’t really want to delete all records of him.
• This problem is referred to as a delete anomaly.

• Alternatives for Storing Data
– Another possible approach would be to store
each student in one row of the table and
create multiple columns to accommodate
each class that he is taking.

• This approach is also fraught with problems:
– How many classes should you allow for in building the table?
– The above table is quite simplified. In reality, you might need
to allow for 20 or more classes (assuming a student could take
many 1-hour classes). Also, more information than just the
course number would be stored for each class. There would
be a great deal of wasted space for all the students taking
fewer than the maximum possible number of classes.
– Also, if you wanted a list of every student taking MGMT-3021,
notice that you would have to search multiple attributes.
Student ID0
Last
Name
First
Name
Phone
No. Class 1 Class 2 Class 3 Class 4
333-33-3333 Simpson Alice 333-3333 ACCT-3603 FIN-3213 MGMT-3021
111-11-1111 Sanders Ned 444-4444 ACCT-3433 MGMT-3021 ANSI-1422
123-45-6789 Moore Artie 555-5555 ACCT-3433 FIN-3213

STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236
Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
• The solution to the preceding problems
is to use a set of tables in a relational
database.
• Each entity is stored in a separate table,
and separate tables or foreign keys can
be used to link the entities together.

• Basic Requirements of a Relational Database
– Every column in a row must be single valued.
• In other words, every cell can have one and only
one value.
• In the student table, you couldn’t have an attribute
named “Phone Number” if a student could have
multiple phone numbers.
• There might be an attribute named “local phone
number” and an attribute named “permanent
phone number.”
• You could not have an attribute named “Class” in
the student table, because a student could take
multiple classes.

• Basic Requirements of a Relational
Database
– The primary key cannot be null.
• The primary key uniquely identifies a specific row
in the table, so it cannot be null, and it must be
unique for every record.
• This rule is referred to as the entity integrity rule.

STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236
Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
• Note that within each table, there are no
duplicate primary keys and no null
primary keys.
• Consistent with the entity integrity rule.

Database
– A foreign key must either be null or
correspond to the value of a primary key in
another table.
• This rule is referred to as the referential integrity
rule.
• The rule is necessary because foreign keys are
used to link rows in one table to rows in another
table.

ADVISORS
1419 Melton Amy 316
1503 Zhang Xi 202
STUDENTS
Advisor
No.
333-33-3333 Simpson Alice 333-3333 1418
111-11-1111 Sanders Ned 444-4444 1418
123-45-6789 Moore Artie 555-5555 1503
Advisor No. is a foreign key in the STUDENTS table. Every
incident of Advisor No. in the STUDENTS table either matches
an instance of the primary key in the ADVISORS table or is null.

Database
– All non-key attributes in a table should
describe a characteristic of the object
identified by the primary key.
• Could nationality be a non-key attribute in the
student table?
• Could advisor’s nationality be a non-key attribute
in the student table?

• The preceding four constraints produce a well-
structured (normalized) database in which:
– Data are consistent.
– Redundancy is minimized and controlled.
• In a normalized database, attributes appear
multiple times only when they function as foreign
keys.
• The referential integrity rule ensures there will be
no update anomaly problem with foreign keys.

• An important feature is that data about various things of
interest (entities) are stored in separate tables.
– Makes it easier to add new data to the system.
• You add a new student by adding a row to the student
table.
• You add a new course by adding a row to the course
table.
• Means you can add a student even if he hasn’t signed
up for any courses.
• And you can add a class even if no students are yet
enrolled in it.
– Makes it easy to avoid the insert anomaly.
• Space is also used more efficiently than in the other
schemes. There should be no blank rows or attributes.

STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236
Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
• Add a
student
here.
• Leaves no
blank
spaces.
• Add a course here.
• Leaves no blank spaces.
• When a particular student enrolls for a
particular course, add that info here.

• Deletion of a class for a student would
cause the elimination of one record in the
student x class table.
– The student still exists in the student table.
– The class still exists in the class table.
– Avoids the delete anomaly.

STUDENT x COURSE
SCID
333333333-1234
333333333-1236
111111111-1235
111111111-1236
Student ID
Last
Name
First
Name
Phone
No.
333-33-3333 Simpson Alice 333-3333
111-11-1111 Sanders Ned 444-4444
123-45-6789 Moore Artie 555-5555
STUDENTS
1234 ACCT-3603 1 MWF 8:30
1235 ACCT-3603 2 TR 9:30
1236 MGMT-2103 1 MW 8:30
COURSES
• Ned still
exists in
the
student
table.
• Even if Ned was the only student in
the class, ACCT-3603 still exists in
the course table.
• If Ned Sanders drops ACCT-3603,
remove Ned’s class from this table.

• There are two basic ways to design well-
structured relational databases.
– Normalization
– Semantic data modeling

– Normalization

• Normalization
– Starts with the assumption that everything is
initially stored in one large table.
– A set of rules is followed to decompose that
initial table into a set of normalized tables.
– Objective is to produce a set of tables in third-
normal form (3NF) because such tables are
free of update, insert, and delete anomalies.
– Approach is beyond the scope of this book
but can be found in any database textbook.

– Normalization

• Semantic data modeling (covered in detail
in Chapter 15)
– Database designer uses knowledge about
how business processes typically work and
the information needs associated with
transaction processing to draw a graphical
picture of what should be included in the
database.
– The resulting graphic is used to create a set
of relational tables that are in 3NF.

• Advantages over simply following
normalization rules:
– Semantic data modeling uses the designer’s
knowledge about business processes and
practices; it therefore facilitates efficient
design of transaction processing databases.
– The resulting graphical model explicitly
represents information about the
organization’s business processes and
policies and facilitates communication with
intended users.

• Creating Relational Database Queries
– Databases store data for people and
organizations.
– To retrieve the data, you query the database
and its tables.
– Chapter 4 of your textbooks provides some
samples of database queries in Microsoft
Access.
– Try these on your own and/or with your
instructor in class.

DATABASE SYSTEMS AND THE FUTURE
OF ACCOUNTING
• Database systems may profoundly affect
the fundamental nature of accounting:
– May lead to abandonment of double-entry
accounting, because the redundancy of the
double entry is not necessary in computer
data processing.
– May also alter the nature of external reporting.
• EXAMPLE: External users could have access to
the company’s database and manipulate the data
to meet their own reporting needs.

OF ACCOUNTING
• The use of accounting information in
decision making will be enhanced by:
– Powerful querying capabilities that
accompany database packages.
– The ability to accommodate multiple views of
the same underlying phenomenon.
– The ability to integrate financial and
operational data.

OF ACCOUNTING
• Accountants must become knowledgeable
about databases so they can participate in
developing the AIS of the future.
• They must help ensure that adequate
controls are included to safeguard the
data and assure its reliability.

Database System

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