Evaluation of Mirek Tudball Club Using Data Science Principles

This report provides a comprehensive analysis of Mirek Tudball Club, utilizing data science principles to address challenges related to match cancellations and revenue management. The report begins with an introduction to data science and its applications, followed by an evaluation of the club's current situation, including an overview of the investigation and the results of the data analysis. The core of the analysis employs decision tree algorithms and Big Data to predict booking cancellations based on factors like weather conditions, offering insights into the probabilities of cancellations under different scenarios. The report also addresses ethical and security considerations related to the club's data practices, emphasizing the importance of data integrity and user privacy. Furthermore, it proposes next steps and potential solutions, including the implementation of machine learning techniques to analyze patterns and forecast cancellations more accurately, and strategies to mitigate financial losses through alternative booking policies and cost-effective maintenance solutions. The report concludes by summarizing the benefits of data science in business decision-making and emphasizing the importance of comprehensive data analysis for informed strategies.

Principles of Data Science for Business

Table of Contents
Introduction......................................................................................................................................1
Evaluation of Mirek Tudball Club.........................................................................................1
Overview of investigation......................................................................................................1
Outcome of analysis ..............................................................................................................2
Ethical as well as security cogitation .....................................................................................4
Next steps & Potential Solutions............................................................................................5
Conclusion.......................................................................................................................................6
References........................................................................................................................................7
Appendix..........................................................................................................................................8
Statistics & Methodology ......................................................................................................8

Introduction
The inter-disciplinary field which makes use of processes, systems, algorithms and
scientific methods for extracting knowledge as well as perceptiveness from both unstructured
and structured data is referred to as data science. It is associated with big data along with data
mining (Benbow and et. al, 2020). This report is based on Mirek Tudball Club which have
around 10,000 fields for matches that are organised at all levels. This report comprises of
assessment, its overview and results of carrying out analysis. Furthermore, it also includes ethical
as well as security considerations and recommendations.
Evaluation of Mirek Tudball Club
As per the rules which are being prescribed according to Tudball involves that in worst
weather situations, it cannot be played. The customers possess right for making cancellation for
reservations which are being made. But this leads to heavy loss to the Club and for this
appropriate measures have to be taken for dealing with revenue failure. On basis of weather
conditions and dataset available data science can be utilised. Decision tree algorithm is two step
process which involves prediction and learning. Within this, learning involves training data and
prediction comprises of predicting response for peculiar data (Bydon and et. al, 2020). Excel
sheet will provide dataset which can be utilised for gaining knowledge on the basis of data and
formulate predictions for eradication of defects. It will aid Club to minimise cancellations which
occurs.
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
1

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)
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.
2
Illustration : Importance of Data Science in Business

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:
3
Illustration 1: Decision Tree Algorithm
Illustration 2: Decision Tree for Sunny and Cold Weather

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 4th 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
4
Illustration 3: Decision Tree for Sunny and Warm Weather

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.
5

 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.
6

References
Books & Journals
Benbow, N. and et. al, 2020. An Iterative Process of Integrating and Developing Big Data
Modeling and Visualization Tools in Collaboration With Public Health Officials.
Bydon, M. and et. al, 2020. Big Data defined: a practical review for neurosurgeons. World
Neurosurgery, 133, pp.e842-e849.
Gendron, J. and Killian, D., 2020. Data citizens: rights and responsibilities in a data
republic. Data Democracy: At the Nexus of Artificial Intelligence, Software
Development, and Knowledge Engineering, p.9.
Gil-Doménech, D. and Berbegal-Mirabent, J., 2020. Making the learning of mathematics
meaningful: An active learning experience for business students. Innovations in
Education and Teaching International, pp.1-10.
Hemdan, E.E.D. and Manjaiah, D.H., 2020. Digital Investigation of Cybercrimes Based on Big
Data Analytics Using Deep Learning. In Deep Learning and Neural Networks:
Concepts, Methodologies, Tools, and Applications (pp. 615-632). IGI Global.
Lu, J., 2020. Data Analytics Research-Informed Teaching in a Digital Technologies
Curriculum. INFORMS Transactions on Education.
Paul, P.K., Solanki, V.K. and Kumar, R., 2020. An Analytical Approach from Cloud Computing
Data Intensive Environment to Internet of Things in Academic Potentialities.
In Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm (pp. 363-381).
Springer, Cham.
Perez, P. and et. al, 2020. An Information Management Strategy for City Data Hubs: Open Data
Strategies for Large Organisations. In Open Cities| Open Data (pp. 289-309). Palgrave
Macmillan, Singapore.
Rivera, R., 2020. Principles of Managerial Statistics and Data Science. John Wiley & Sons.
Rizk, A. and Elragal, A., 2020. Data science: developing theoretical contributions in information
systems via text analytics. Journal of Big Data, 7(1), pp.1-26.
Sainz Sujet, P., 2020. Review of Data Visualisation: A Handbook for Data Driven Design: Data
Visualisation. A Handbook for Data Driven Design, by Andy Kirk, LA, Sage
publications, 2019, 312 pp., $106.93 (hardcover), ISBN: 978-1-5264-6892-5. Structural
Equation Modeling: A Multidisciplinary Journal, pp.1-3.
Online
Data Science for Business – 7 Major Implementations of Data Science in Businesses. 2020.
[Online]. Available through: <https://data-flair.training/blogs/data-science-for-
business/>.
7

Appendix
Statistics & Methodology
Machine learning algorithms are being utilised for analysing précised behaviour of
individuals for generating real time recommendations to their clients. Different algorithms are
being used to formulate decisions. By going through above discussion, machine learning will be
used by Mirek Tudball Club for solving their problem and it can be carried out by making use of
following steps:
 Collection of data from past events when matches took place in what weather conditions
and who were the players means gender and try to identify the pattern in which
cancellation occurred (Rizk and Elragal, 2020).
 Try to formulate a function which utilises given information that is being available for
each like in sunny and warm weather there is higher probability that match will be
cancelled. So alternatives like if team plays in this situation then half amount can be
refunded. (This will be profitable for Mirek Tudball Club instead of cancellation of
match).
 There has to be a surety that by usage of algorithms that predictions which are made are
accurate and will yield apt results.
Through the usage of Decision Tree Algorithm, prediction becomes easy as by
visualisation, situations can analysed in an appropriate manner which will enable to have apt
results. According to available dataset of Mirek Tudball Club, it was identified that a single
entity did not lead to cancellation but two entities resulted within this.
8

Here, sky and temp variables are dependent entities which results within cancellation.
Decision Tree algorithm can provide the illustration for each condition like it can be sunny &
warm, cloudy & cold, cloudy & warm and many others. Depending upon results attained
predictions can be made in this context for each situation (Sainz Sujet, 2020). This will lead
Mirek Tudball Club to identify the worst situation in which maximum cancellations occurred
like in sunny and warm weather.
9
Illustration 4: Dataset of Mirek Tudball Club

Illustration 5: Decision Tree for Sunny & Warm
This shows the maximum cancellations. In addition to this, there are higher chances of
cancellations with respect to females as per dataset. But by appropriate use of strategies this can
be minimised.
10