MBUA512: Knowledge Discovery in Databases (KDD) - IT Assessment Answer

MBUA512:  IT Assessment Task

METHOD: KNOWLEDGE DISCOVERY IN DATABASES (KDD)

Step 1: Goal identification MBUA512

The first step of the KDD is goal identification from the customer’s perspective. As part of this project, I have decided to limit the scope to a fairly small scenario with an unusually small but representative database. This is created in order to test a hypotheses that I already know the conclusion of in order to better understand the process; as well as see if existing data can be useful for future predictions. The key areas I have decided to focus on is the changes in the number of travellers entering New Zealand and the number of nights in Motel stays in New Zealand. (I have selected motels in particular, as it reflects solely travellers via car most accurately) I will compare these two variable with historic data on car rentals registrations. By identifying the relationship strength between these three variables, we can make predictions for rental car prices. 

Step 2: Selection  MBUA512

With the goal in mind, the next step of the KDD is to understand application domains involved and the knowledge that's required and to select a target data set or subset of data samples on which discovery is be performed. 

Application domain 1: Tourism -> International travel and migration. International travel and migration statistics give the number of overseas visitors, New Zealand resident travellers, and permanent and long-term migrants entering or leaving New Zealand. Variables found: Average number in New Zealand each day by travel purpose and county.

Step 3: Preprocessing MBUA512

Next, I set us to cleanse and preprocess data by deciding strategies to handle missing fields and alter the data as per the requirements. Key areas looking towards eliminating are incomplete, noisy, and inconsistent data.

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