Data at the Core
of the Enterprise
Objectives
 Define of database systems
 Introduce data modeling and SQL
 Discuss emerging requirements of
database systems
DATA
?
INFORMATION
Attributes of data
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Sharable
Moveable
Secure
Accurate
Timely
Relevant
Data hierarchy
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Bits
Characters
Fields (columns)
Records (rows)
Files (table)
Database
Why build a database?
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Handle large amounts of data
Satisfy multiple users
Make information retrieval faster
Make data input faster
Provide greater accuracy
Database versus Database
Management System (DBMS)
 Database is a self-describing collection
of integrated files
 A DBMS is a complex computer
program that acts as a data librarian,
supervising the transfer of data between
the end user and the database
Advantages of DBMS
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More info from the same data
Reduction of data duplication
Improved data integrity
Programs are independent of the data
format
 Sharing of data resources
…and disadvantages
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Added expense
More hardware may be needed
If it crashes….
Sophisticated design and programming
required
 Additional training
 Security is critical
Relational model
 Relation? Attribute? Tuple?
 Keys
 Primary and foreign
 Referential integrity
 Relational algebra
Relational DB rules
 Every row must have exactly the same
number of columns (fields or attributes)
 Each row can have only one value stored in
each column (fields or attributes)
 A column must contain the same kind of value
in every row of that column
 No two rows can be exactly the same
 The order of the rows or of the columns can’t
be used to provide information
Terminology
Data
Processing
Informal
Relational DB
Formal
Relational DB
File
Table
Relation
Record
Row
Tuple
Field
Column
Attribute
Data modeling
 Purpose: control and visualization
 Process: gathering requirements
 Results: forms and diagrams
Normalization
 Purpose:
 Avoid anomalies
 Reduce redundancy
 Process:
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Successive application of rules
Bottom-up (data drives process)
Move from first through fifth normal form
Does it make more or less tables?
Entity relationship modeling
 List the entities or objects in the
environment
 People, things, transactions
 Describe the relationship between them
 A single row in table A can be related to
how many rows in table B (one or many)
 A single row in table B can be related to
how many rows in table A (one or many)
ERD questions
 What are the subjects/objects of the
business?
data entities
 What unique characteristic(s) distinguishes
each object from others of same type?
primary key
 What characteristics describe each object?
attributes
 How do you use this data?
controls & meaning
ERD questions
 Over what period of time are you interested in
this data?
cardinality & time dimensions
 Are all instances of each object the same?
supertypes, subtypes, aggregations
 What events occur that imply associations
between objects?
relationships (cardinality & degree)
 Is each activity or event always handled the
same way or are there special
circumstances?
integrity rules, cardinality, time
SQL
 Definition (DDL)
 CREATE, ALTER, DROP
 Manipulation (DML)
 SELECT, INSERT, UPDATE, DELETE
 What’s the most used sql command?
General format of SELECT
SELECT [DISTINCT] item(s)
FROM table(s)
[WHERE condition]
[GROUP BY columns]
[HAVING condition]
[ORDER BY row(s)]
Emerging data requirements
Complex
Video Streams
Graphics
Video
Audio
HTML/
SGML
Spatial Data
Time Series
Unstructured
Images
Text
Structured
Audio Streams
Current RDBMS
Simple
Summary
 Defined of database systems
 Introduced data modeling and SQL
 Discussed emerging requirements of
database systems