Tour Databasing Inquiries

Design a data model that will conform to the following criteria:

• Propose an efficient data structure that may hold the tour operator's data using a normalization process. Describe each step of the process that will enable you to have a 2nd Normal Form data structure.

The database in question provides sufficient data for operational consistency but the redundancy of certain data impedes the general efficiency of the system in place. Therefore, normalization is a major priority for the tour operating company. Specifically, the database is overburdened by duplicate customer records, each of which is created at the time that a new tour is booked. This denotes that the system is decidedly inefficient in presenting data on the whole of our customer base.

First, we propose the use of framing as a data structure as a way of refining the representation of data. According to the text by Minsky (1974), individual frames are used to distill bits of data before drawing a connection between theme. According to Minksy, "Attached to each frame are several kinds of information. Some of this information is about how to use the frame. Some is about what one can expect to happen next. Some is about what to do if these expectations are not confirmed....

We can think of a frame as a network of nodes and relations. The 'top levels' of a frame are fixed, and represent things that are always true about the supposed situation. The lower levels have many terminals -- "slots" that must be filled by specific instances or data." (Minsky, p. 1)
In our emergent data strategy, the top levels would refer to immutable data such as employee names and ID#s. Contrary to the previously existing strategy of databasing, this approach calls for all tour information, including tour clients and all related data, to be subordinated under tour operator accounts. This is consistent with the method of data structuring proposed by Chapple (2011), which indicates that avoiding duplicate data requires the minimization of duplicate columns from the initial data table and, consequently, the creation of "separate tables for each group of related data and identify each row with a unique column (the primary key)." (Chapple, p. 1)

The text goes on to indicate that "the first rule dictates that we must not duplicate data within the same row of a table. Within the database community, this concept is referred to as the atomicity of a table. Tables that comply with this rule are said to be atomic." (Chapple, p. 1)

This means that the best way to manage the…