Question

What data processing models would you prescribe for each of the following: handling airline reservations, handling total sales by department for each day of operations, and measuring the quality of cookies coming off an assembly line?

Answer 1

1. Handing airline reservations: Entity-relationship model

It is a data processing model which connects the relationships between the real world entities. The people, places, and things about which data points are stored are referred to as entities, each of which has certain attributes that together make up their domain.

In case of airlines, the entities are passengers, booking agents, airports, legs, flight schedules, flight costs, itinerary payments etc. Each of the entities has attributes such as passengers having passenger details- name, phone number, email address; airports having attributes as origin airport code, destination airport code, airport names, location etc.

When a reservation is made by a passenger, the airline database maps the cardinality or relationships between entities like passenger and destination airport and schedule information.

2. Handling total sales by department for each day of operations: Object-oriented database model

To understand how sales and operations can be effectively handled in an object-oriented data model, let us consider an example.

Say a retail store has several departments like women, men and kids wear. In an object-oriented data model, objects and their associated features and methods are linked to create a thread of process estimation.

In the following example, object1 are different ranges, namely women's wear, men's wear and kids wear. Object2 can be Sales activity column featuring product code, product name, sales associate, date of sale, price etc. Object3 is Sales report having features month of sale, product code, vendor, revenue etc. The instances jotted against every feature when the sale of a product is made, tells about the numerics that each product has made, basically sales/revenue.

Incorporating these tables of objects, the total sales of the day of the retail store is calculated and also measured to which product and department sold most and least. Further analysis of this object-oriented data model reveals estimations about the total revenue earned and forecast for marketing and selling products.