PIR MEHR ALI SHAH ARID AGRICULTURE UNIVERSITY
University Institute of Information Technology
Database Systems
Credit Hours:
4(3-2)
Prerequisites:
Course Learning Outcomes (CLOs)
At the end of course the students will be able to:
1. Explain fundamental database concepts.
2. Design conceptual, logical and physical database schemas
using different data models.
3. Identify functional dependencies and resolve database
anomalies by normalizing database tables.
4. Use Structured Query Language (SQL) for database
definition and manipulation in any DBMS
None
Domain
C
C
BT Level*
2
5
C
2
C
4
*BT- Bloom’s Taxonomy, C=Cognitive domain, P=Psychomotor domain, A=Affective domain
Course Contents:
Basic database concepts, Database approach vs file based system, database architecture, three
level schema architecture, data independence, relational data model, attributes, schemas, tuples,
domains, relation instances, keys of relations, integrity constraints, relational algebra, selection,
projection, Cartesian product, types of joins, normalization, functional dependencies, normal
forms, entity relationship model, entity sets, attributes, relationship, entity-relationship
diagrams, Structured Query Language (SQL), Joins and sub-queries in SQL, Grouping and
aggregation in SQL, concurrency control, database backup and recovery, indexes, NoSQL
systems.
Course Objective:
The objective of the course is to present an introduction to database management systems, with
an emphasis on how to organize, maintain and retrieve - efficiently, and effectively information from a DBMS.
Learning Outcomes: Upon successful completion of this course, students should be able to:
• Describe the fundamental elements of relational database management systems
• Explain the basic concepts of relational data model, entity-relationship model, relational
database design, relational algebra and SQL.
• Design ER-models to represent simple database application scenarios
• Convert the ER-model to relational tables, populate relational database and formulate SQL
queries on data.
• Improve the database design by normalization.
• Familiar with basic database storage structures and access techniques: file and page
organizations, indexing methods including B tree, and hashing.
Teaching Methodology:
Lectures, Written Assignments, Practical labs, Semester Project, Presentations
Courses Assessment:
Exams, Assignments, Quizzes. Course will be assessed using a combination of written examinations.
Reference Materials:
1. Database Systems: A Practical Approach to Design, Implementation, and Management, 6th
Edition by Thomas Connolly and Carolyn Begg
2. Database Systems: The Complete Book, 2nd Edition by Hector Garcia-Molina, Jeffrey D.
Ullman, Jennifer Widom
3. Database System Concepts, 6th Edition by Avi Silberschatz, Henry F. Korth and S.
Sudarshan.
4. Database Management Systems, 3rd Edition by Raghu Ramakrishnan, Johannes Gehrke
Week
1
Contents Theory
Practical
File Based System, Database Approach,
Roll in Data Base Environment, History of data
base Management System, Advantages and
Disadvantages Of DBMSs
2
The Relational Model
SQL
Displaying Table Structure
Selecting Specific Columns
Arithmetic Expressions
Operator Precedence
Defining a Column Alias
The Relational Model
SQL Statements
Defining a Column Alias
Concatenation Operator
Eliminating Duplicate Rows
How to build and manage database?
Database Systems, File based system, DBMS
approach
What is File based approach? Limitations of
File based approach
DBMS approach, Advantages of DBMS, Cost
and Risks Factors.
Three Level ANSI-SPARC Architecture
Restricting and Sorting Data
External level, Conceptual Level, Internal Level Limiting Rows Selected
Disadvantages of Three Level Architecture
Comparison Operators
Other operators (BETWEEN, IN,
LIKE, IS NULL)
3
4
5
Entity Relationship modeling
o
o
o
o
o
o
o
6
Entity
Attributes and its types
Identifier
Primary Key
Candidate Key
Relationship
Degree of Relationship
 Unary
 Binary
 Ternary
 Quaternary
Cardinality of Relationship
o One-to-one relationship
o One-to-many relationship
o Many-to-many relationship
 Minimum/Maximum Cardinality
o Optional one
o Optional Many
o Mandatory one
o Mandatory Many
 CASE STUDY (One in class and two as
assignment)
7
 Enhanced ERD
o Super Type
o Sub Type
o Generalization
o Specialization
o Attribute Inheritance
o Relationship Inheritance
o Constraints
Views creation
Logical Operators and Rules of
Precedence
Order by Clause
Single-Row Functions
Character functions
Number functions
Date functions
Conversion function
Group Functions
– AVG
– COUNT
– MAX
– MIN
– STDDEV
– SUM
– VARIANCE
Displaying Data from Multiple
Tables
Sub queries






8
Completeness Constraint
Total Specialization
Partial Specialization
Disjoint Constraint
Disjoint Rule
Overlap Rule
CASE STUDY ASSIGNMENT
Transformation of (E)ER Model into Relational
Model
Attributes
 Simple
 Composite
 Multivalued
Entities
 Regular
 Weak
 Associative
Relationship
 Unary
 One-to-one
 One-to-Many
 Many-to-Many
 Binary
 One-to-one
o Minimum
/Maximu
m same
on both
o OptionalMandator
y
 One-to-Many
 Many-to-Many
•
•
•
•
•
Insert rows into a table
Update rows in a table
Delete rows from a table
Merge rows in a table
Control transactions
 Ternary
 Quaternary
Super Type
Subtype
 CASE STUDY of Transformation
9
o
o
o
o
MID TERM
 Data Normalization
Characteristics of Suitable Relation
Advantages of Suitable Relations
Goal of Normalization
Data Anomalies
 Insertion Anomaly
 Deletion Anomaly
 Updation Anomaly
Creating and Managing Tables
10
o Definitions of Some Terms
 Functional Dependency
 Partial Dependency
 Transitive Dependency
o First Normal Form
o Second Normal Form
o Third Normal Form
 CASE STUDY
•
•
•
•
•
11
o Relational Algebra
o Writing relational calculus
queries in relational algebraic
query.
Assignment
12
o
o
o
o
o
 Physical Design
Purpose
Goal
Inputs
Decisions
Designing Field
Describe a view
Create a view
Retrieve data through a view
Alter the definition of a view
Insert, update, and delete data
through
a view
• Drop a view
o
o
o
o
Physical records
Page
De-normalization
Partitioning
 Horizontal
 Vertical
13
o Objectives during selection of data type
o Controlling Data Integrity
 Data type
 Default value
 Range control
 Null value control
 Referential integrity
o File Organization
 Factors
o Sequential File Organization
o Indexed File Organization
 Hybrid
 Key range
 Hash
o Data replication
Creating indexes
Hashed File Organization
14
15
16
17
Introduction to Mongo DB
Database Security Database Recovery
Stored procedures
Project demos
Final Exam
Hands On Practice in Mongo DB
Sequence
Index
Synonym
Controlling User Access
Creating users and granting
privileges to users.
Recovery
Triggers