MIS 301
Information Systems in Organizations
Dave Salisbury
[email protected] (email)
http://www.davesalisbury.com/ (web site)
Databases & Data Modeling
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Data as a resource
Samples of how databases are set up in
organizations
Basic logical modeling of data
Basic physical modeling of data
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Data Integrity
Normalization
Logical Data Elements
Personnel
Database
Employee
Record 1
Payroll
File
Benefits
File
Employee
Record 2
Employee
Record 3
Employee
Record 4
Name SS Salary Name SS Salary Name SS Salary Name SS Salary
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Physical Data Access
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(Primary) key fields
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Sequential Access (Tape)
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Unique identifier for a record
Stored in order by key field
Can only be retrieved/stored in that order
Direct Access (Disk)
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Hashed File Organization
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Key transformed into physical address using algorithm
Indexed Sequential Access Method (ISAM)
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Direct access using indexes
Sequential when doing batch runs
Disadvantages of File Processing
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Program-Data Dependence
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Data Redundancy (Duplication of data)
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Different systems/programs have separate copies
of the same data
Limited Data Sharing
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All programs maintain metadata for each file they
use
No centralized control of data
Excessive Program Maintenance
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80% of of information systems budget
Duplicate (Redundant) Data
Problems with Data Redundancy
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Waste of space to have duplicate data
Causes more maintenance headaches
The biggest Problem:
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When data changes in one file, could cause
inconsistencies
Compromises data integrity
Lack of coordination and central control
Non-standard file formats
Database
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Central repository of shared data
Data is managed by a controlling agent
Stored in a standardized, convenient
form
Requires a database management
system (DBMS)
Advantages of Database Approach
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Program-Data Independence
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Minimal Data Redundancy
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Different users get different views of the data
Enforcement of Standards
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Leads to increased data integrity/consistency
Improved Data Sharing
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Metadata stored in DBMS, so applications don’t need to
worry about data formats
All data access is done in the same way
Improved Data Quality
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Constraints, data validation rules
Modeling Reality
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A database must mirror the real world if it is
to answer questions about the real world
Data Modeling is a design technique for
capturing reality
STUDENT
Social_Security_No
Name
Major
Entity-Relationship Modeling
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One type of data modeling
Represents data in terms of:
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Entities
Relationships
Entity-Relationship Modeling
Entity-something (real or abstract) that
can be identified in a user’s work
environment that can be distinguished
from other things.
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Entity Class-(i.e. CUSTOMER)
Entity Instance-(e.g. FRED FLINSTONE)
Entity-Relationship Modeling
Attributes (a.k.a. properties). Describe
the characteristics of entities.
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EMPLOYEE_NAME
EMPLOYMENT_DATE
Entity-Relationship Modeling
Primary keys - identify instances of
entities, a.k.a. key attributes
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SOCIAL_SECURITY_NUMBER
Entity-Relationship Modeling
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Relationships imply constraints on how
many entities may occur on one side (or
the other) of a given relationship.
Types of Relationships
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one-to-one 1:1
one-to-many 1:N
many-to-many N:M
Notation in an ER diagram
ENTITY
Something about which
you want to keep data.
RELATIONSHIP
How things you want to
keep data about are tied
together.
•Attribute – Something you want to store about an entity.
•Primary Key – Uniquely identifies an entity (e.g. SID).
Entity-Relationship Modeling
Places/
Placed by
Customer
Order
Contains/ is
Contained in
Product
Relational Databases
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Relations (a.k.a. tables)
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Each row is unique (entity instance)
Order is unimportant
Each column represents one thing
(attribute)
Entries are from the same domain (e.g.
student)
Relational Databases
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Keys
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Primary key (uniquely identifies a record)
Composite key, a.k.a. Concatenated key
(two elements combined are unique)
Foreign key (links tables/relations)
Data Integrity
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Rules to make sure your data is valid
Entity integrity constraint
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Referential integrity
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Primary key cannot be null
Ensures valid relationships between data
Cannot add a row with no parent
Cannot delete a parent without deleting child
(cascading)
Domain Integrity
Data Interrelationships
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Dependencies and determinants
Anomalies
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Insertion
Deletion
Update
Normalization
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First normal form
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Second normal form
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No repeating groups
No partial dependencies
Third normal form
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No transitive dependencies
M:N Relationships in Relational Model
Places/
Placed by
Contains/ is
Contained in
Order
Order Line
Customer
Product
Contains/ is
Contained in
How this looks in Access
1
OrderID
OrderDate
CustomerID
1
ORDER LINE
OrderID
ProductID
Quantity
PRODUCT
ProductID
Description
Price
Weight
Supplier
8
ORDER
8
CustomerID
FirstName
LastName
Address
City
State
Zip
Telephone
1
8
CUSTOMER