This document discusses key concepts related to databases and database management systems (DBMS). It defines a database as an organized collection of data, and a DBMS as software that manages databases. The document then discusses different types of database users, the purpose of using a DBMS over file systems, different data models, and SQL statements for defining database structure and manipulating data.

1. General Concepts
• Database definition
– Organized collection of logically related data
• Data
– Known facts
– Types: text, graphics, images, sound, videos
• Database management system (DBMS)
– Software package for defining and managing a
database

2. Introduction to DBMS
Data
Consists of raw facts, and when organized may be
transformed into information
Database
A collection of related data organized to meet users
needs
Database management system (DBMS)
A group of programs that manipulate the database
and provide an interface between the database and
the user of the database.
A Database Management System (DBMS) is a
software system designed to store, manage, and
facilitate access to databases.

3. Flat Files
Characteristics:
• Data is stored as records in regular files
• Records usually have a simple structure and fixed
number of fields
• For fast access may support indexing of fields in the
records
• No mechanisms for relating data between files
• One needs special programs in order to access and
manipulate the data

4. Why Study Databases?
• Databases are useful
– Many computing
applications deal with large
amounts of information
– Database systems give a set
of tools for storing,
searching and managing this
information
• Databases in CS
– Databases are a ‘core topic’ in
computer science
– Basic concepts and skills with
database systems are part of
the skill set you will be
assumed to have as a
Computer science graduate

5. Database
Basics
Traditional database
organizes data in a
hierarchy.
A field is the smallest
element. Fields are
within a record.
Records are organized
in a data file.
Database is a collection
of data files.

6. File System DBMS
1 Less no. of files used 1 Large no. of files used
2 Doesn’t provide Security 2 Better Security, username and passward
3 Data redundancy is problem
Loss of integrity-(accurate and
consistent data)
3 Redundancy problem is solved
Data is independenat
4 Data is isolated 4 Data is integrated
5 Data access takes lot of time 5 Less time
6 Concurrency control is not possible
Single user system
6 Multiple user access data at same time
7 Little preliminary design 7 Vast permanent design
8 Transaction concept not used
Eg:
8 Important in DBMS
Eg:
9 9

7. =
Files vs. DBMS
If we were to use files, we
would have to :
• Must write special code for different queries
• Must protect data from inconsistency due to multiple
concurrent users
• Must manage crash recovery in some special-purpose
manner
• Must provide good methods for access control

9. Databases
• Web indexes
• Library catalogues
• Medical records
• Bank accounts
• Stock control
• Personnel systems
• Product catalogues
• Telephone directories
• Train timetables
• Airline bookings
• Credit card details
• Student records
• Customer histories
• Stock market prices
• Discussion boards
• and so on…

10. Database users
• The people who interact with the database.
• End users
– Use the database system to
achieve some goal -
updating, inserting or
modifying data from the
database
• Application developers
– Write application program
to allow end users to
interface with the database
system
• Database Administrator
(DBA)
– manages the database
system
• Database systems
programmer
– Writes the database
software itself

11. The people who interact with the database…
1. End users – updating, inserting or modifying data from the
database
 naïve users – only access the database based on their demand and
access level, unaware of the DBMS, use predefined queries
 sophisticated users – have complex requirements and queries,
know the structure of the DBMS, engineers, scientists…
 casual users – occasional users, need different data every time
they come, use sophisticated queries…

12. Users …
Database Administrator - responsible to manage the
database and the DBMS, authorize access, determine
HW and SW resources.
Database Designer – identifies the data to be stored
and design the structure of the database.
System Administrator – responsible for the entire
computer system of the organization.

13. Why not text files, Spreadsheets..??
• Data integrity
• Redundancy
• Outdated data
• Data size
• Retrieval
• Searching
• Filtering
• Protecting data from unauthorized use
• Protecting data from becoming corrupt

14. Why Study Databases??
• Shift from computation to information
– always true for corporate computing
– Web made this point for personal computing
– more and more true for scientific computing
• Need for DBMS has exploded in the last years
– Corporate: retail swipe, “customer relationship mgmt”,
“supply chain mgmt”, “data warehouses”, etc.
– Scientific: digital libraries, Human Genome project,
NASA Mission to Planet Earth, physical sensors, grid
physics network

15. Why Use a DBMS?
• Reduced application development time.
• Data independence
• Efficient data access.
• Data integrity under updates.
• Concurrent access
• Recovery from crashes.
• Security
• Uniform data administration.

16. Databases make these people happy ...
• DBMS vendors, programmers
– Oracle, IBM, MS, Sybase, …
• End users in many fields
– Business, education, science, …
• DB application programmers
– Build enterprise applications on top of DBMSs
– Build web services that run off DBMSs
• Database administrators (DBAs)
– Design logical/physical schemas
– Handle security and authorization
– Data availability, crash recovery
– Database tuning as needs evolve

17. Levels of Abstraction
Users
View 1 View 2 View 3
Conceptual Schema
Physical Schema
DB
• Many views:
– Views describe how users see the
data.
• conceptual (logical) schema
– Conceptual schema defines logical
structure of DB and relationship
between tables.
• physical schema:
– Physical schema describes how
data is stored in a DB.

18. Data Independence
• Applications insulated from how
data is structured and stored.
• Logical data independence:
Protection from changes in
logical structure of data.
• Physical data independence:
Protection from changes in
physical structure of data.
View 1 View 2 View 3
Conceptual Schema
Physical Schema
DB

19. Example: University Database
• Conceptual schema:
– Students(sid: integer, name: string, login: string,
age: integer)
– Courses(cid: string, cname: string, credits: integer)
– Enrolled(sid: integer, cid:string, grade: string)
• Physical schema:
– Relations stored as unordered files.
– Index on first column of Students.
• External Schema (View):
– Course_info

20. Data Entities, Attributes, and
Keys
• Entity
• A generalized class of people, places, or things (objects) for
which data are collected, stored, and maintained
• E.g., Customer, Employee
• Attribute
• A characteristic of an entity; something the entity is identified by
• E.g., Customer name, Employee name
• Keys
• A field or set of fields in a record that is used to identify the
record
• E.g, A field or set of fields that uniquely identifies the record

21. Project Number Description Dept. Number
155 Payroll 257
498 Widgets 632
226 Sales manager 598
Dept. Number Dept. Name Manager SSN
257 Accounting 421-55-99993
632 Manufacturing 765-00-3192
598 Marketing 098-40-1370
SSN Last Name First Name Hire Date Dept. Number
005-10-6321 Johns Francine 10-7-65 257
549-77-1001 Buckley Bill 2-17-79 650
098-40-1370 Fiske Steven 1-5-85 598

22. Relation schema:
A set of attributes is called a relation schema (or relation scheme).
A relation schema is also known as table schema
It is the logical definition of a table.
Relation schema defines what the name of the table is.
This includes a set of column names, the data types associated with each
column.
A database schema is the collection of relation schemas for a whole
database.
A database schema can be described a blueprint of a database that
outlines the way data is organized into tables.

23. SQL statements are divided into two major categories:
data definition language (DDL) and
data manipulation language (DML).
Data Definition Language (DDL) statements are used
to define the database structure or schema. Some examples:
* CREATE - to create objects in the database
* ALTER - alters the structure of the database
* DROP - delete objects from the database
* TRUNCATE - remove all records from a table, including
all spaces allocated for the records are removed
* COMMENT - add comments to the data dictionary
* RENAME - rename an object

24. Data Manipulation Language (DML) statements are
used for managing data within schema objects.
Some examples:
* SELECT - retrieve data from the a database
* INSERT - insert data into a table
* UPDATE - updates existing data within a table
* DELETE - deletes all records from a table, the space for the
records remain
* MERGE - UPSERT operation (insert or update)
* EXPLAIN PLAN - explain access path to data
* LOCK TABLE - control concurrency

25. Data Control Language (DCL) statements.
* GRANT - gives user's access privileges to database
* REVOKE - withdraw access privileges given with the
GRANT command

26. Transaction Control (TCL) statements are used to
manage the changes made by DML statements.
* COMMIT - save work done
* SAVEPOINT - identify a point in a transaction to which you
can later roll back
* ROLLBACK - restore database to original since the last
COMMIT

27. What are Data Models?
Type of Data Models.
A model is a representation of reality, 'real world' objects and events,
associations. It is an abstraction
Types:
Object Based Data Models
Record Based Data Models
Physical Data Models

28. Object Based Data Models
• Entity-Relationship
• Object Oriented
• Semantic
• Functional

29. Record Based Logical Models
Record based logical models are used in describing data at the logical and
view levels.
Each record type defines a fixed number of fields, or attributes, and each field
is usually of a fixed length.
The three most widely accepted record based data models are:
• Hierarchical Model
• Network Model
• Relational Model

30. Physical Data Models
Physical data models describe how data is stored in the
computer, representing information such as record
structures, record ordering, and access paths. There are
not as many physical data models as logical data models,
the most common one being the Unifying Model.

33. One mark question:
1. State functions of DBA?
2. State different data abstraction levels provided by DBMS?
3. Define database system:
4. Difference between file system & DBMS:
5. What are views: Explain level of views.
6. What is role of Naïve user in DBMS?
7. Who all are dbms users?
8. What is DML?
9. What is DDL?
10.What is DCL?
11.What is TCL?
12.Define Data Dictionary?
13.Advantage of DBMS?
14.Disadvantage of DBMS?
15.Define Data Model?
16.Types of DML?
17.Differentiate procedural DML & Non-procedural DML:

34. Five mark question: