The document provides an overview of the database design for Air India. It includes assumptions, initial and final ER diagrams, tables with functional dependencies, and sample SQL queries to demonstrate basic operations on the database. The database design consists of 10 normalized tables to store information about countries, states, contacts, passengers, flight schedules, routes, airfares, aircrafts and transactions. The document describes the tables, relationships between them and provides examples of queries to retrieve flight details, passenger information and perform analytics on bookings and sales.

1. Air India Database Design
DBMS (CSN-351)
Group Number - 1
Abhishek Jaisingh 14114002
Amandeep 14114008
Tirth Patel 14114036
​Table of Contents
ER Diagram 2
Assumptions 2
Initial Schema Diagram 3
Tables with FDs 4
Final Schema Diagram 8
Basic Operations with SQL queries and results 9
1

2. ER diagram
Assumptions
1. There is a route code table not listed as separate table in our design, which has
information about all the intermediate airports in a journey with specific route code.
2. A person can only book 1 ticket per transaction. A new transaction is required again to
book more tickets.
3. Fare for the each flight in AirFare table is calculated separately using the Route of the
flight.
2

3. Initial Schema diagram
3

4. Tables with functional dependencies
Country [BCNF]
Primary Key: CtID
CtID → CountryName
CREATE TABLE ​`Country`
(
`CtID`​ INT NOT NULL AUTO_INCREMENT,
`CountryName`​ varchar​(​32​)​ NOT NULL,
PRIMARY KEY ​(​`CtID`)
);
State [BCNF]
Primary Key: StID
StID → StateName | Country
CREATE TABLE ​`State`
(
`StID`​ INT NOT NULL AUTO_INCREMENT UNIQUE,
`StateName`​ varchar​(​32​)​ NOT NULL,
`Country`​ INT NOT NULL,
PRIMARY KEY ​(​`StID`​),
FOREIGN KEY ​(​`Country`​)​ REFERENCES ​`Country`​(​`CtID`)
);
Contact_Details [BCNF]
Primary Key: CnID
CnID → Email | Mobile | State
CREATE TABLE ​`Contact_Details`
(
`CnID`​ INT NOT NULL AUTO_INCREMENT,
`Email`​ varchar​(​50​)​ NOT NULL,
`Mobile`​ varchar​(​16​)​ NOT NULL,
`State`​ INT NOT NULL,
PRIMARY KEY ​(​`CnID`​),
FOREIGN KEY ​(​`State`​)​ REFERENCES ​`State`​(​`StID`)
4

5. );
Passenger [BCNF]
Primary Key: PsID
PsID → Name | Address | Age | Nationality | Contacts
CREATE TABLE ​`Passenger`
(
`PsID`​ INT NOT NULL AUTO_INCREMENT,
`Name`​ varchar​(​32​)​ NOT NULL,
`Address`​ varchar​(​64​)​ NOT NULL,
`Age`​ INT NOT NULL,
`Nationality`​ varchar​(​16​)​ NOT NULL,
`Contacts`​ INT NOT NULL,
PRIMARY KEY ​(​`PsID`​),
FOREIGN KEY ​(​`Contacts`​)​ REFERENCES ​`Contact_Details`​(​`CnID`)
);
Transaction [BCNF]
Primary Key: TsID
TsID → BookingDate | Passenger | Flight
CREATE TABLE ​`Transaction`
(
`TsID`​ INT NOT NULL AUTO_INCREMENT,
`BookingDate`​ DATETIME NOT NULL,
`Passenger`​ INT NOT NULL,
`Flight`​ INT NOT NULL,
PRIMARY KEY ​(​`TsID`​),
FOREIGN KEY ​(​`Passenger`​)​ REFERENCES ​`Passenger`​(​`PsID`​),
FOREIGN KEY ​(​`Flight`​)​ REFERENCES ​`Flight_Schedule`​(​`FlID`)
);
Flight_Schedule [2NF]
Primary Key: FlID
FlID → FlightDate | Departure | Arrival | AirCraft | NetFare
Departure → FlightDate
5

6. CREATE TABLE ​`Flight_Schedule`
(
`FlID`​ INT NOT NULL AUTO_INCREMENT,
`FlightDate`​ DATE NOT NULL,
`Departure`​ DATETIME NOT NULL,
`Arrival`​ DATETIME NOT NULL,
`AirCraft`​ INT NOT NULL,
`NetFare`​ INT NOT NULL,
PRIMARY KEY ​(​`FlID`​),
FOREIGN KEY ​(​`AirCraft`​)​ REFERENCES ​`AirCraft`​(​`AcID`​),
FOREIGN KEY ​(​`NetFare`​)​ REFERENCES ​`AirFare`​(​`AfID`)
);
Note : This table is in 2NF due to the derivation of FlightDate from Departure attribute
which is trivial. Removing this dependency by adding extra table only for FlightDate
enhances the overhead for queries. Keeping it in this form results in very little reduction
in memory efficiency.
AirFare [BCNF]
Primary Key: AfID
AfID → Route | Fare
CREATE TABLE ​`AirFare`
(
`AfID`​ INT NOT NULL AUTO_INCREMENT,
`Route`​ INT NOT NULL,
`Fare`​ INT NOT NULL,
PRIMARY KEY ​(​`AfID`​),
FOREIGN KEY ​(​`Route`​)​ REFERENCES ​`Route`​(​`RtID`)
);
Route [BCNF]
Primary Key: RtID
RtID → Airport | Destination | RouteCode
CREATE TABLE ​`Route`
(
`RtID`​ INT NOT NULL AUTO_INCREMENT,
`Airport`​ varchar​(​32​)​ NOT NULL,
`Destination`​ varchar​(​32​)​ NOT NULL,
`RouteCode`​ varchar​(​16​)​ NOT NULL UNIQUE,
PRIMARY KEY ​(​`RtID`)
6

7. );
Note : Here RouteCode will be is unique number recognizing the route of the flight
between given 2 airports.
AirCraft [2NF]
Primary Key: AcID
AcID → Ac_Type | Capacity | Mfg_Date
Ac_Type → Capacity
Note : To convert into ​BCNF​, this table is decomposed into 2 new following tables
AirCraft​ and ​AirCraft_Type​.
AirCraft [BCNF] (from decomposition)
Primary Key: AcID
AcID → Ac_Type | Ac_Type | Mfg_Date
CREATE TABLE ​`AirCraft`
(
`AcID`​ INT NOT NULL AUTO_INCREMENT,
`Ac_Type`​ INT NOT NULL,
`Mfg_Date`​ DATE NOT NULL,
PRIMARY KEY ​(​`AcID`​),
FOREIGN KEY ​(​`Ac_Type`​)​ REFERENCES ​`AirCraft_Type`​(​`ActID`)
);
AirCraft_Type [BCNF] (from decomposition)
Primary Key: ActID
ActID → Type | Capacity
CREATE TABLE ​`AirCraft_Type`
(
`ActID`​ INT NOT NULL AUTO_INCREMENT,
`Type`​ varchar​(​32​)​ NOT NULL,
`Capacity`​ INT NOT NULL,
PRIMARY KEY ​(​`ActID`)
);
7

8. Final Schema Diagram
This is final schema diagram after decomposition. These 10 tables are made in our Air India
database design.
8

9. Basic Operations
Here are some basic operations listed that our database provides. Each functionality is shown
with corresponding sample SQL query and screenshot.
1. List all the aircrafts older than '2' years (can be used for expiry dates or
maintenance date)
SELECT ​AcID​,​ ​Mfg_Date​,​ ​Type
FROM ​AirCraft​ INNER JOIN ​AirCraft_Type​ ON ​(​AirCraft​.​Ac_Type​ ​=​ ​AirCraft_Type​.​ActID​)
WHERE YEAR​(​CURDATE​())​ ​-​ YEAR​(​Mfg_Date​)​ ​>​ 2
2. List all the flights in database from airport 'New Delhi' to airport 'Bangalore'
SELECT ​FlId​,​ ​FlightDate​,​ ​Fare​,​ ​Departure​,​ ​Arrival
FROM ​((​Flight_Schedule​ INNER JOIN ​AirFare​ ON ​(​Flight_Schedule​.​NetFare​ ​=​ ​AirFare​.​AfID​)))
INNER JOIN ​Route​ ON ​(​Route​ ​=​ ​RtID​)
WHERE ​Airport​ ​=​ ​'New Delhi'​ AND ​Destination​ ​=​ ​'Bangalore'
9

10. 3. List all the passengers for flight no. '5'
SELECT NAME​,​ ​Age​,​ ​Mobile
FROM ​Transaction​ INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
WHERE ​Flight​ ​=​ ​5
ORDER BY NAME
4. List all the minor (age less than 18) travelling in flight no. '5'
SELECT ​Name​,​ ​Age​,​ ​Mobile​,​ ​Address​,​ ​StateName​,​ ​CountryName
FROM ​Transaction​ INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
INNER JOIN ​State​ ON ​(​State​ ​=​ ​StID​)
INNER JOIN ​Country​ ON ​(​CtID​ ​=​ ​Country)
WHERE ​Flight​ ​=​ ​5​ AND ​Age​ ​<​ ​18
ORDER BY NAME​,​ ​Age
10

11. 5. Total Fare collected from date '2016-10-01' to date '2016-10-20'
SELECT SUM​(​Fare​)
FROM ​Transaction​ INNER JOIN ​Flight_Schedule​ ON ​(​Flight​ ​=​ ​FlID​)
INNER JOIN ​AirFare​ ON ​(​NetFare​ ​=​ ​AfID​)
WHERE DATE ​(​BookingDate​)​ BETWEEN ​'2016-10-01'​ AND ​'2016-10-20'
6. Total number of tickets booked from date '2016-10-10' to date '2016-11-25'
SELECT COUNT​(​PsID​)​ AS ​Tickets
FROM ​Transaction​ INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
WHERE DATE ​(​BookingDate​)​ BETWEEN ​'2016-10-10'​ AND ​'2016-11-25';
7. Number of persons travelling airport 'New Delhi' from date '2016-11-1' to date
'2016-11-30'
SELECT COUNT​(​PsID​)​ AS NUM_CUSTOMERS
FROM ​Route​ INNER JOIN ​AirFare​ ON ​(​RtID​ ​=​ ​Route​)
INNER JOIN ​Flight_Schedule​ ON ​(​AfID​ ​=​ ​NetFare​)
INNER JOIN ​Transaction​ ON ​(​Flight​ ​=​ ​FlID​)
INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
WHERE DATE ​(​FlightDate​)​ BETWEEN ​'2016-11-1'​ AND ​'2016-11-30'​ AND ​Airport​ ​=​ ​'New Delhi';
11

12. 8. Number of persons reaching at 'New Delhi' from date '2016-11-1' to date
'2016-11-30'
SELECT COUNT​(​PsID​)​ AS NUM_CUSTOMERS
FROM ​Route​ INNER JOIN ​AirFare​ ON ​(​RtID​ ​=​ ​Route​)
INNER JOIN ​Flight_Schedule​ ON ​(​AfID​ ​=​ ​NetFare​)
INNER JOIN ​Transaction​ ON ​(​Flight​ ​=​ ​FlID​)
INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
WHERE DATE ​(​FlightDate​)​ BETWEEN ​'2016-11-1'​ AND ​'2016-11-30'​ AND ​Destination​ ​=​ ​'New Delhi';
9. Number of persons with flights from 'New Delhi' to 'Bangalore' from date
'2016-11-1' to date '2016-11-30'
SELECT COUNT​(​PsID​)​ AS NUM_CUSTOMERS
FROM ​Route​ INNER JOIN ​AirFare​ ON ​(​RtID​ ​=​ ​Route​)
INNER JOIN ​Flight_Schedule​ ON ​(​AfID​ ​=​ ​NetFare​)
INNER JOIN ​Transaction​ ON ​(​Flight​ ​=​ ​FlID​)
INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
WHERE DATE ​(​FlightDate​)​ BETWEEN ​'2016-11-1'​ AND ​'2016-11-30'​ AND ​Airport​ ​=​ ​'New Delhi'
AND ​Destination​ ​=​ ​'Bangalore';
10. Provide State wise analysis of sales of flight tickets
SELECT ​StateName​,​ ​Count​(​PsID​)​ AS ​Tickets
FROM ​Transaction​ INNER JOIN ​Passenger​ ON ​(​Transaction​.​Passenger​ ​=​ ​PsID​)
INNER JOIN ​Contact_Details​ ON ​(​Contacts​ ​=​ ​CnID​)
INNER JOIN ​State​ ON ​(​State​ ​=​ ​StID​)
GROUP BY ​StateName
ORDER BY ​Count​(​PsID​)​ DESC;
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