Question

Author a 2-page paper(single-space), 11 point Calibri font) discussing the following item: Discuss the best practices for developing data modles that can be used for large database applications such as an airline ticketing system. Cite your sources in the ACM format.

Answer 1

Answer:-

Airlines Data Model (OADM) delivers an IATA standards-based data management platform for building "data capital" by enabling the capture and organization of data from across the enterprise and beyond. By leveraging Oracle’s deep expertise in data management, OADM provides a platform that is modern, relevant, and topical. Data can be consolidated and organized from key areas such as passenger service systems (PSS) and customer loyalty, baggage and ancillary services, social media, flight operations and departure control systems (DCS), scheduling and global distribution systems (GDS), maintenance and repair (MRO), and back office applications such as finance. Oracle Advanced Analytics with OADM can provide new insights and enable data driven decisions to improve operational efficiencies, tailor products and services, or even identify new sources of competitive advantage. OADM is available as an add-on to Oracle Database Cloud Service (DBCS) or Oracle Relational Database Enterprise Edition. OADM is not dependent on any particular vendor's source applications and can be used in any application environment, including Oracle Cx Cloud Services.

FLIGHT CREDIT CARD DETAILS flight id FLIGHT DETAILS profile_id (FK) card_number card_type expiration_month expiration year airline id airline name from location to location departure time arrival time duration total seats flight id (FK) flight_departure_date price available seats TICKET INFO PASSENGER PROFILE ticket id profile_id (FK) profile_id password first name last name address tel no email_id flight id (FK) flight departure_date (FK) status

Besides details enumerated above, airlines should be keeping following additional data in their airline reservation system:

• Their inventory for next six months, which is airlines’ flight schedule on different routes and aircraft seating capacity;
• Data on Authorised Travel Agents along with their deposits and authorised limits of sale and their commission etc
• Data on Consolidators and Tour Operators and their accounts if they are involved in ticket sale.
• Accounts of GDS (Global Distributors) such as Sabre, Abacus and Galileo etc.
• Data of frequent flyers and their accounts
• Data of business / first class passengers profile if such a service is being provided
• Data on loyal customers and prospective customers
• Seasonal variation in passenger traffic and class wise yield
• Credit card related data
• Results of any surveys etc pertaining to passenger preferences or tickets buying patterns.
• Code share and inter airline agreement details

There may be quite a few more than this, which an individual airline may develop for its own brand.

Airline reservation systems predate modern data structures as we understand them today. They are structured in a completely different way than modern databases. They reference specific memory spaces with largely unstructured data fields, rather than the modern concepts of objects, classes, and attributes.

After the flights are flown, for the purposes of analysis by the airline, this data is converted into a modern structured database, usually SQL. For some reason most US airlines use a program called BRIO to analyze the data after it is pulled using SQL. I haven’t encountered any other industries that use BRIO even though it is no way airline-industry specific.