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The notion of flight is central to this system, thus we’ll have a flight table. This means that we have to determine a primary key and, at first sight, the flight number would be a good candidate but it’s not and the reason for this is that the flight number is not painted on an aircraft; it’s only a logical way of expressing the movement of a plane between two airports, and also the persons or companies related to this movement. We note that the flight number is kept short three or four digits for improved reference on all printed matter and on airport information screens; thus, this flight number is only meaningful when accompanied by supplemental information, like the airline code (AQ) or company name, and a date. Keeping in mind that there will be other tables associated with this flight table, we have two choices here for the primary key: create a surrogate key (an artificial primary key whose value is not derived from other table’s data) use a combination of columns airline_id, flight_number, departure_moment It is better to create a surrogate key, id. This id will be propagated to the related tables in just one column, which could help to speed up retrieval times because there is just one field to compare between tables. Using the flight’s id will also simplify the writing of queries. Of course we include the flight number the information known to the public in the flight table but not as a primary key. table: reservation column name sample value *flight_id 34 *passenger_id 1302 web_site_quick_reference KARTYU ticket_number 014 88417654 ticket_issued_moment 2007-01-01 12:00 booking_agency_id 1 ticket_refundability_id 1 ticket_type_id 1 seat 19A section_id 2 It would be a mistake to include columns such as passenger1, passenger2 or seat_1a, seat_1b in the flights table. This is why we use the reservation table to hold passenger information related to a specific flight. This table could also be named flight_passenger.
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table: passenger column name sample value *id 1302 last_name Smith first_name Peter passport_info CDN234234 table: crew column name sample value *id 9 category_id 1 last_name Murray first_name Dan Passengers and crew members cannot be physically merged into one table even if they belong to the same flight because the set of columns used to describe a passenger diverges from the one associated to a crew member. We’ll cover in the Sample Queries section how to produce a combined list of all persons on a plane. table: flight column name sample value *id 34 airline_id 1 number 456 departure_moment 2007-10-02 22:45 arrival_moment 2007-10-03 11:30 departure_airport_id 1 arrival_airport_id 2 plane_id 302 meal_supplier_id 9 number_meals 2 departure_gate 74 arrival_gate B65 boarding_moment 2007-10-02 22:10 status_id 1
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table: crew_category column name sample value *id 1 description Pilot To avoid columns like pilot_last_name, copilot_first_name, we form a crew_category table. See also the related flight_crew table later in this chapter. table: ticket_refundability column name sample value *id 1 description non-refundable table: flight_status column name sample value *id 1 description boarding table: event column name sample value *id 1 description repair If we need to include other types of events in the model, this event table will have to be renamed as something more precise like plane_event, and a new name will be needed for our current plane_event table that is used to associate an event with a plane. Themed Tables These tables are more comprehensive than the code tables. Each one refers to a specific theme that needs more columns than a simple code table. table: plane column name sample value *id 302 airline_id 1 brand_id 1 model_id 2 description Charlie This table identifies which aircraft belongs to which airline, with the description being an internal means of describing this particular aircraft within the airline. Other fields like an aircraft serial number can be added here.
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Code Tables Usually the following tables are designed first because they are easier to model and they are needed for establishing the relations from more complex tables. table: airport column name sample value *id 1 international_code YUL description Montreal-Trudeau The airport table could contain other columns like the address, phone, and website. table: airline column name sample value *id 1 description Air-Quebec table: plane_brand column name sample value *id 1 description Fontax We avoid naming this table as brand because it’s a too generic name. table: meal_supplier column name sample value *id 9 description Montreal Chef Service table: booking_agency column name sample value *id 1 description Fantastic Tour Again, this table could have more details about the agency, like phone and address. We could also merge this table with meal_supplier table by adding a code identifying the type of company, but it’s not done in the present model. table: ticket_type column name sample value *id 1 description one-way
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Preliminary List of Data Elements We list here the data elements as they can be deduced from the document gathering phase. In many cases, they are not in a format already suitable for the final model because they are prefixed with a table name. For example, a data element identified as pilot_last_name will become the column last_name in the. pilot table. Sample values and more detailed information about each data element appear in the next section. Data elements flight_departure_moment seat_id flight_arrival_moment plane_section departure_airport_code ticket_refundability arrival_airport_code gate_id airline_code boarding_time airline_name max_number_in_cabin_bags airport_name max_number_registered_bags plane_brand max_weight_registered_bags_kg plane_model tag_id pilot_last_name ticket_issued_on pilot_first_name number_meals flight_attendant_last_name web_site_quick_reference flight_attendant_first_name meal_supplier passenger_last_name plane_id passenger_first_name plane_event passenger_id plane_event_start_moment booking_agency_name plane_event_end_moment ticket_number flight_status Tables and Sample Values To prepare the list of tables, we start with the physical objects or persons we can observe in the sentences built from the documents gathering phase. Then we have a look at all the elements and build new tables to accommodate them. In the following table descriptions, the table layout is followed by design comments when appropriate.
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Will need to be coded (id and description). Two meals are served on this flight. Air Quebec has arrangements with Montreal Chef Service for the preparation and delivery of food. The data elements obtained from the above sentence are: number_meals airline_name meal_supplier Air Quebec owns four Fontax APM-300 aircraft but aircraft #302 (code-named Charlie) is scheduled for repairs in October 2007. The data elements obtained from the above sentence are: airline_name plane_brand plane_model plane_id description plane_event plane_event_start_moment plane_event_end_moment Each plane is affectionately nicknamed, the element for this will be “description”. About the repairs, we generalize them with the concept of events, having a starting and ending moment. Passenger Smith can use the quick reference code A6BCUD and his last name to access his flight information on the airline web site. The data elements obtained from the above sentence are: passenger_last_name web_site_quick_reference
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The sections available on a plane depend not only on the plane model but also on the airline. This ticket is non-refundable. The data element obtained from the above sentence is: ticket_refundability Flight 456 can be boarded at gate number 74, 35 minutes before takeoff. The data elements obtained from the above sentence are: flight_number gate_id boarding_time In economy class, passengers are entitled to one bag inside the cabin and two registered bags total weight 50 kg max. Mr Smith has one registered bag, bearing the tag AQ636-84763. The data elements obtained from the above sentence are: plane_section max_number_in_cabin_bags max_number_registered_bags max_weight_registered_bags_kg tag_id We have detected that “class” is a synonym for “section”. There are information screens in the airport that indicate the state of each flight: on time, boarding, delayed, or cancelled. The data element obtained from the above sentence is: flight_status
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Chapter 6 [ 77 ] The pilot on this flight is Dan Murray and the flight attendant is Melanie Waters. Other crew members are to be confirmed. The data elements obtained from the above sentence are: pilot_first_name pilot_last_name flight_attendant_first_name flight_attendant_last_name We should generalize using the notion of a crew category. Peter Smith buys a ticket for this flight from Fantastic Tour, Inc., a booking agency. The ticket number is 014 88417654. This is a one-way ticket. The data elements obtained from the above sentence are: passenger_first_name passenger_last_name booking_agency_name ticket_number ticket_type We’ll also need a primary key for the passenger and probably for the booking agency if we don’t use its code. Should the ticket itself be represented in a table, or will the ticket number be part of something more general like a reservation? For this flight, Mr. Smith is seated at 19A, located in the economy section of the plane. The data elements obtained from the above sentence are: passenger_last_name seat_id plane_section
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Supplemental Case Study [ 76 ] airport_name flight_departure_moment We need to indicate whether the airport is for departure or arrival. The airport code for Montreal-Trudeau is YUL and the one for Charles de Gaulle is CDG. The data element obtained from the above sentence is: airport_code Should we use the airport_code as a primary key? Maybe not, due to space considerations. This flight is scheduled to land at 11:30 the day after (local time). The data element obtained is: flight_arrival_moment Do we need to split the date and time into two fields? Probably not, to benefit from date and time calculations functions (how many hours and minutes takes a flight, taking the date into account). An aircraft model APM-300 from Fontax services this flight. The data elements obtained from above sentence are: plane_model plane_brand Do we need to associate the plane model to a flight, but also to which specific plane. (There can be more than one APM-300.)
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Supplemental Case Study Now, it’s time to apply our newly learned principles to a completely different theme. We upgrade from cars to planes, covering a simple airline system. This chapter’s case study does not pretend to encompass the full collection of data from real airline it’s only a sample. Nonetheless, we’ll see that the principles we learned previously can be applied to build and refine a correct and coherent data structure. Normally, each airline has its own information system. We assume here that we have got the mandate to build an information system that encompasses many airlines. Results from the Document Gathering Phase After reviewing the airline system’s current website, a booking agent’s website, some electronic tickets, and boarding passes, we gather a large amount of information. We’ll first express this information with sentences which present the system and data exchange on a rather high level. Each sentence is followed by a list of the data elements which we can deduce from it. An element can be present in more than one sentence. Refer to the Tables and Sample Values section for more details about each data element. There are also some notes that will help us in the naming and grouping phase. Flight 456 of Air Quebec leaves Montreal-Trudeau airport at 22:45 on October 2nd, 2007 heading for Paris’s Charles de Gaulle. The following are the data elements that can be obtained from the above sentence: flight_number airline_name
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