Principles of Data Science for Business

Evaluation of Mirek Tudball Club

According to the rules prescribed by Tudball, in extreme weather conditions, the activity cannot be played. Customers have the right to cancel reservations under such circumstances, which can lead to significant financial losses for the Club. To address this issue and mitigate revenue shortfalls, appropriate measures must be taken. Utilizing data science, particularly by analyzing weather conditions and available datasets, can be an effective strategy. The Decision Tree algorithm, a two-step process involving learning and prediction, is particularly useful in this context. Learning involves training on existing data, while prediction focuses on forecasting responses for specific data points (Bydon et al., 2020). For example, an Excel sheet containing relevant datasets can be leveraged to gain insights and make informed predictions, helping the Club reduce cancellations. To further enhance these strategies, coursework help can provide additional resources and support, ensuring the development of robust data-driven solutions for minimizing cancellations.

Overview of investigation

For dealing with issues faced by Mirek Tudball Club, data science will be used as this will enable them to have business intelligence for formulating smarter decisions, predict outcomes, assess formulated decisions and automate processes (Data Science for Business – 7 Major Implementations of Data Science in Businesses, 2020). In certain condition Tudball can not be played. Because of unsuitable weather condition people prefer to cancel their bookings. To find prediction of booking cancellation, previous cancellation data along with cancellation reasons can be used in tool like Big Data. Big Data can be used to get better prediction of booking cancellation. Along with Big Data, Decision Tree also can be used to represent result of prediction to make better understanding. We have used this two processes to get effective prediction data for company to keep revenue constant and profitable. The reason for selecting Big Data is related to the features of Big Data. It is efficient tool to analyse large size data with high complexities. Big Data is also efficient to find better result with complex cross related data so, I have selected this tool in data analysis process.

(Source: Data Science for Business – 7 Major Implementations of Data Science in Businesses, 2020)

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Outcome of analysis

Decision tree algorithm can be utilised as it maps probable results for series of choices which are being identified. This assists individuals or firms for weighing possible actions on the basis of probabilities, costs and benefits. Different nodes are present within this and each illustrate different aspects (Gendron and Killian, 2020). Chance nodes are denoted by circle which illustrates probabilities for outcomes. Decision nodes are illustrated via square that show decisions which have to be made. End node shows final results of decision path.

With respect to dataset of Mirek Tudball Club, the decision tree comprises of root node which is weather and according to different conditions it will be identified whether match will be played or not.

An instance can be taken with respect to dataset of Mirek Tudball Club like when there is sunny and cold then probability of match cancellation is 50% in context of males but 60% of female match will be cancelled (Gil-Doménech and Berbegal-Mirabent, 2020). For both these conditions decision tree has been illustrated below:

Depending upon these values from dataset, the probability for match cancellation is very high. On basis of dataset other instance is being taken for account i.e. sunny and warm condition. With respect to that the decision tree is illustrated below:

From above decision tree it can be seen that in sunny and warm environment 90% of males will not play tudball and 80% of females will not play this game. This implies that there are higher conditions in which individuals will cancel matches (Hemdan and Manjaiah, 2020). Similarly, as per different situations predictions can be made with respect to this. But it is clear from above that appropriate strategies or policies have to be formulated that will ensure that if match is cancelled then also Mirek Tudball Club do not go through any financial crisis as they have to pay maintainenance cost each day. 

Ethical as well as security cogitation

The Mirek Tudball Club organise matches on weekdays and weekends. An instance can be taken to understand the ethical aspects like if team A has made booking for say 4^th Feb 2020 and someone other asks for booking for the same date. If organisers of Club allot field for both by thinking that, might be later cancel their booking then it is not ethically correct. These aspects have to be seriously considered by Mirek Tudball Club. Security issues are related with dataset which is present with them if any alterations are being made within this then their predictive analysis will go wrong on basis of which hypothesis will be derived (Lu, 2020). So, it is necessary that systems must be protected by making use of strong passwords and services from cloud can be utilised for storing it.

Next steps & Potential Solutions

Mirek Tudball Club need to look for options through which problems faced by them (illustrated above) can be solved. Here, they opt for making use of machine learning which refers to sub-area of artificial intelligence that implies capability of information technology systems for finding answer to problems through recognition of patterns within the dataset. In example shown in previous questions the two conditions were taken and that also for 100 entries present within the dataset (Paul, Solanki and Kumar, 2020). This implies that entire prediction have to be made based on all the probable conditions which are given and all values from last few years to analyse patterns. For an instance , if 'sky' is cloudy and 'temp' is cold then females will cancel their bookings but it might not be same males. This denotes that for making predictions weather forecasting has also to be utilised along with patterns. The reason behind this is that appropriate strategies can be formulated by Mirek Tudball Club to deal with cancellations. Steps which will be utilised by Club through machine learning are illustrated below:

• Examination of dataset with respect to data present and analysis that have to carried out by taking into consideration all the aspect associated with this.
• Identifying all patterns along with statistical relationship among entities like 'sky', 'temp' , 'cancelled', 'customer_type' and 'gender'. They are entities which have to be considered and their pattern has to be identified.
• Through usage of statistical relationship as well as pattern for predicting whether match will be cancelled or not.

This leads Mirek Tudball Club to have analysis of whether match will be cancelled or not and this mostly depends on the weather forecasts. Therefore, both the aspects have to be considered (Perez, and et. al, 2020). Strategies to deal will cancellation and minimisation of cost have been shown below:

• At present as per CEO, on making a prediction that match will be cancelled they can offer team or players with half refund if they keep their reservation.
• Suppose, if it has been predicted that match will be cancelled then also field has to be maintained and for this, Club is making use of Yortulis Beneficialis variants of moss which needs fertilizing and watering on daily basis. This denotes that high cost is involved. For this, instead of grass which is being used alternative like artificial turf can be utilised whose maintenance cost is almost negligible (Rivera, 2020).

Conclusion

From above it can be concluded that data science aids businesses within formulation of appropriate decisions by making predictions with respect to data available with them. It enables them to identify what replications they will go through as well as what are there assets. For this it is crucial that algorithm must be utilised by analysing entire dataset.

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