The rise of information and communication technologies and the advent of social media platforms allow travelers to express their opinions and share their air travel experiences. The table describes a dataset that is collected from an online platform where travelers can evaluate their travel experiences with airlines.

• Data mining can be used to analyze the dataset and understand the public opinions of the quality of airline services, with the objective to improve customers’ air travel experiences.

(i) Give one example of descriptive data mining in this context and discuss how it can be used to achieve the stated objective.
(ii) Give one example of predictive data mining in this context and discuss how it can be used to achieve the stated objective.

• Suggest two additional variables that can be included in formulating data analytics solutions for understanding customers’ air travel experiences. Explain the rationale of their inclusion.
• Assume that there are two interesting findings obtained from the analysis:

* For economy class, most travelers who recommend the airlines give a rating of 4 or above to Value for Money.
* Leisure travelers have a lower mean rating of Inflight Entertainment than other types of travelers.

• Identify one limitation of using the dataset stated in Table 1 to understand air travel experiences and propose one (1) way to address the limitation.