Course Introduction



Introduction
Relational Database Systems:
 Creating a relational database (DDL)
 Formulating SQL queries (DML)
 Embedded SQL
 Relational algebra
 Relational model, relational integrity, etc.
Data Modeling:
 Entity-relationship model
 Converting an E-R schema into a relational schema
Web-Based Database Applications
 PHP and MySQL
 Drupal Content Management System (CMS)
1
Overview of data management
After this lecture, you should be able to:
 Understand the differences between
Information and Data.
 Understand the differences between Database
and Database Management System (DBMS).
Why do we need them?
 Understand Data Modeling in general,
Relational Model in particular.
 Complete the Assignment 1.
Introduction
2
Data vs. Information

Introduction
From data.gov
“Data are values or sets of values representing a specific
concept or concepts. Data become "information" when
analyzed and possibly combined with other data in order
to extract meaning, and to provide context. The
meaning of data can vary according to its context”
(Source: Federal Enterprise Architecture Data Reference
Model).
3
Information Management



Introduction
Modeling an enterprise, which is an
application-world with
 Entities (e.g., students, courses)
 Relationships (e.g., Garfield is taking
CS275)
Creating a database with a database
management system (DBMS).
Manipulating and Maintaining a database
4
Data Encoding
Information
Data Modeling
Entities, Relationships, etc.
Numbers, Strings, Records, Pointers, etc.
Bits, Bytes, Pages, etc.
Electronic Charges, Magnetic polarization, etc.
Introduction
5
Database vs. DBMS


Introduction
A database is an integrated collection of data.
A database management system (DBMS) is a
software package designed to create and
manage a database.
 The data stored in a database are organized
according to the data model supported by
the DBMS.
 A relational database, for example, stores
the data in a collection of tables.
6
DBMS Functions






Introduction
Data definition
Data manipulation
Security and data integrity
Recovery and concurrency control
Data dictionary
Performance tuning
7
Advantages of Integrated
Data Management








Introduction
Data sharing
No (logical) redundancy of stored data
Simple and efficient data access
Reduced application development time
Data integrity and security
Concurrent access, recovery from crashes
Uniform data administration
Economy
8
Problems with Storing Data in Files





Introduction
Data stored in different files cannot be easily
related.
Accessing desired records may not be easy.
Efficient protection against inconsistency
caused by multiple concurrent users not easy
to implement.
Effective crash recovery not supported.
Security and access control not enough.
9
Why Study Databases?



Introduction
Shift from computation to information
 scramble to webspace
 scientific applications
Datasets increasing in diversity and volume.
 Digital libraries
 interactive video
 Environmental protection
DBMS encompasses most of CS
 OS
 Theory
 Data Structures, Algorithms, Languages
 Multimedia
10
Data Model



A data model is a collection of concepts for
describing data.
The relational model of data is the most widely
used data model today.
 Main concept: relation, basically a table
with rows and columns.
 Relations can represent entities with
attributes and associations among entities.
A schema is a description of a particular
collection of data, using a given data model.
Introduction
11
Example: Student Relation

Student (sid: string, name: string, login: string,
age: integer, gpa: real)
Introduction
12
Data Encoding
Information
Data Modeling
Entities, Relationships, etc.
Numbers, Strings, Records, Pointers, etc.
Bits, Bytes, Pages, etc.
Electronic Charges, Magnetic polarization, etc.
Introduction
13
Levels of Abstraction

Views (external
schema) describe how
users see the data.


The conceptual
schema defines logical
structure of the data.
The physical schema
describes how the data
are stored on physical
devices (files and indexes
used).
View 1
View 2
View 3
Conceptual Schema
Physical Schema
* External and Conceptual schemas are defined using DDL (Data
Definition Language);
* Data is modified/queried using DML (Data Manipulation
Introduction
Language).
14
Example: University Database



Conceptual schema:
 Students(sid: string, name: string, login: string, age:
integer, gpa: real)
 Courses(cid: string, cname: string, credits: integer)
 Enrolled(sid: string, cid: string, grade: string)
Physical schema:
 Relations stored as unordered files.
 Index on first column of Students.
External Schema (View):
 Course_info(cid: string, no_of_enrollment: integer)
 Students_gpa_greater_than_3(sid: string, name:
string, gpa: real)
Introduction
15
Data Independence

Applications insulated from how data is structured and
stored.

Logical data independence
Protection from changes in logical structure of data.
Old applications should work.

Physical data independence
Protection from changes in physical structure of data.
Data should be accessible even when storage media
and/or formats change.

Introduction
Data Independence is one of the most important
benefits of using a DBMS!
16
Layered Architecture of a DBMS
Query Optimization
and Execution
Relational Operators
Files and Access Methods
Buffer Management
Disk Space Management
DB
Introduction
17
Three Tier Software System Architecture
Presentation Tier
Logic Tier
End users
Applications
Clients
DBMS
Server
Data Tier
Database
Introduction
18
Languages


Introduction
Host Languages
 C, C++
 Java, C#
 PHP, Python
Data Sublanguages (DSLs): DSL = DDL + DML
 SQL
• Data Definition Language (DDL)
Used to define the structure of a database
• Data Manipulation Language (DML)
Used to access and manipulate data
 CODASYL DBTG Language
19
DBA (Database Administrator)






Introduction
Defines the conceptual schema
Defines the internal schema
Talks to the users
Defines backup and recovery procedures
Conducts performance tuning
Conducts security management
20
Summary






A database is an integrated collection of data shared by
possibly multiple applications.
A DBMS is a general software package for creating and
managing a database.
A DBMS supports query languages, recovery from system
crashes, concurrent access, quick application development,
data integrity, and security.
Levels of abstraction give data independence.
A DBMS typically has a layered architecture.
DBAs hold responsible jobs and are paid well.
Introduction
21