MIS 301
Information Systems in
Organizations
Dave Salisbury
[email protected] (email)
http://www.davesalisbury.com/ (web site)
Things to know about Database




Translating a business situation into a
logical data model
Translating a logical data model into a
relational database
Using access QBE to query relational
databases (in Access)
Querying multi-table databases (in
Access)
Databases & Data Modeling



Data as a resource
Basic logical modeling of data
Basic physical modeling of data


Data Integrity
Normalization
Student ROI (Return on Investment)





Your investment of time and effort in this course will
result in your being able to answer these questions:
How do knowledge workers use Access QBE to
query a single-table database?
How is Access QBE used to query multiple-table
databases?
How do knowledge workers use logical modeling to
create effective relational database systems?
How do you as a user participate in helping to build
a database for your organization?
The Basics
(this’ll come up again in technology)

Binary Digits (Bit)


Byte


0 or 1
8 bits (usually), combined to mean something
Coding Schemes


ASCII – American Standard Code for
Information Interchange
EBCDIC – Extended Binary Coded Decimal
Interchange Code
The Data Hierarchy







The data hierarchy is a
way of organizing
stored data in
progressively larger
levels of complexity
Bit
Character
Field
Record
File
Database
File Processing Systems



Before the development of database systems, most
organizations used file processing systems.
With file processing, each application uses it own set
of files.
Even though files may be related by an application,
they are not necessarily stored or managed together.
Traditional file processing problems

Program-Data Dependence


Data Redundancy (Duplication of data)


Different systems/programs have separate copies
of the same data
Limited Data Sharing


All programs maintain metadata for each file they
use
No centralized control of data
Excessive Program Maintenance

As much as 80% of of information systems
budget
Duplicate (Redundant) Data
Data redundancy is bad because…



Waste of space to have duplicate data
Causes more maintenance headaches
The biggest Problem:




When data changes in one file, could
cause inconsistencies
Compromises data integrity
Lack of coordination and central control
Non-standard file formats
Database




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

Program-Data Independence


Minimal Data Redundancy


Different users get different views of the data
Enforcement of Standards


Leads to increased data integrity/consistency
Improved Data Sharing


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

Constraints, data validation rules
Relational Data Model



The relational data model was created by E. F. Codd in the early
1970’s.
It is a method of logically storing data in a database that is
independent of the method used to physically store the data.
Relational database management systems (RDBMS) are the
most popular way of storing large amounts of data.
The Relational Data Model





The relational data model stores data in one
or more tables corresponding to entities.
Tables consist of records which correspond
to rows in the tables.
Records store data on a single instance of an
entity.
A record consists of one or more fields.
Fields are often referred to as attributes and
correspond to columns of the tables.
Related Tables



Each table has a unique field called the
primary key.
Tables are related via matching fields.
If the primary key in one table is the
reference key to another table, it is referred
to as a foreign key.
Using a Database




Designing a database and storing data in it is
just the first step.
The power of a database comes from the
capability to work with the data stored there.
The primary method of using a database is
to query it.
The standard way of doing this for a RDBMS
is to use the Structured Query Language
(SQL), or for Access, a Query Language
known as Query by Example (QBE).
Modeling Reality


A database must mirror the real world if it is
to answer questions about the real world
Hence, we must first model reality using data
modeling
STUDENT
Social_Security_No
Name
Major
Building a logical data model



Initial step to building a relational
database – don’t focus on technology
at this point
Identify the things an organization
needs to track and how they are
related
Focus on the “big picture” – things one
cares about and how they are related
Entity-Relationship Modeling



One type of data modeling
Entities – things you want to keep
track of
Relationships – how those things are
related to one another
Notation in an ER diagram
ENTITY
RELATIONSHIP
Something about which
you want to keep data.
How things you want to keep data
about are tied together.
How to depict how many of one thing is related to how many of another.
= zero
or
or
= one
or
or
= many
Entity-Relationship Modeling


Relationships imply constraints on how
many entities may occur on one side
(or the other) of a given relationship.
Types of Relationships



one-to-one 1:1
one-to-many 1:N
many-to-many N:M
Sample E-R Model
Places/
Placed by
Customer
Order
Contains/ is
Contained in
Product
The goal is a well-designed relational
database





Tables
Each row is unique (entity instance – one
example of a given entity)
Order is unimportant (can be sorted using
queries later)
Each column represents one thing about the
entity instance - attribute
Entries are from the same domain (e.g.
student)
Well-designed relational databases

Multiple tables


One for each class of things one cares about
Avoid redundancy



Each class of things gets its own table
Only information about the relevant class goes in a
table
Design to limit redundancy


Redundancy leads to waste of storage space
Redundancy causes modification anomalies on
inserts, deletes or updates
Data Integrity


Rules to make sure your data is valid
Entity integrity constraint


Primary key cannot be null
Referential integrity



Ensures valid relationships between data
Cannot add a row with no parent
Cannot delete a parent without deleting
child (cascading)
Relational database keys



Primary key (uniquely identifies a
record)
Composite key, a.k.a. Concatenated
key (two elements combined are
unique)
Foreign key (links tables/relations)
Many-to-many relationships






Can’t exist in a relational database
They do, however, exist in real life
How to translate them into something that CAN be
modeled in a relational database?
Make an intersection table between the two tables in
a many-to-many relationship
Use one element of two tables to tie them together
put in the intersection table
The resulting table will either have a defined key, or
will use a combination of the keys of the two tables
being tied together
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
CUSTOMER
1
ORDERED_
PRODUCT
OrderID
ProductID
Quantity
8
OrderID
OrderDate
CustomerID
PRODUCT
ProductID
Description
Price
Weight
Supplier
1
8
ORDER
8
CustomerID
FirstName
LastName
Address
City
State
Zip
Telephone
1