If you don´t know DataScience, stop reading and leave this assignment to someone

If you don´t know DataScience, stop reading and leave this assignment to someone who does. If you do know data science and have access to R or Python for example please check the following points which must be incorporated in the 6 page paper (excluding first page, table of content, bibliography and attachments)
See further a brief introduction which I already wrote. Use it as a reference in order to be complete.
It must be a predictive data analysis based on a car leasing company, if you dont have access to this data, leave it to someone who does have access. You are a controller in a car leasing company who has the following assignment based on data science, be clear in why this data scientific problem is relevant.
The following 10 points must be covered in this paper:
1 Description of the data scientific problem that you want to do with specialists and help of experts and how you wish to solve this data scientific problem with them.
2 an assessment of an international car leasing company (your organization) on how to use data science within your organization and why it is relevant from a controller perspective.
3 a description of the data for the solution of the data scientific problem. (use R or Python and show graphs’
4 A brief description of the role that DCAM, DevOps, open source, in and external datasources and cloud could have in this specific case.
5 Explain why your dataset and your analysis is relevant in a controlling context, include the goal and need of your analsysis in the context of a strong controller. (use outcomes of R or Python and but them as figures/attachments in this assignment)
6 Describe which analysis you are doing (regression, KNN, etc.) and why you chose for example KNN analysis instead of another. (Use R or Python for example and show how you have done it in charts/figures)
*7 IMPORTANT (Theoretical part) as your analysis must be a predictive model
use a decision matrix with alternative hypothesis and zero hypothesis with two type errors. Explain which V´s you use from big data in your analysis. Explain which of the 5 analysis are used from Gartner´s theory. Explain whether your analysis is deductive or inductive and relate this explanation on the Wisdom pyramid of Tutill.
8 Explain where your analysis fits within the push left principal and what the touchpoints are with creating shared value of this theoretical model.
9 Explain for your analysis the role of flexibility, training MSE, test MSE, Bias and Variance and the trade off between bias and variance. (Use R or Python for example and show proof in attachments)
10 explain the impact of the results of your analysis and what they mean (conclude)
*7 CONFUSION MATRIX explain your gamma Y, type I error ay (e.g. false positive FP), Type II error beta (1-Y) (e.g. false negative FN)
LOOK AND FEEL + START MADE BY ME:
Table of contents
1. Introduction 4
1.1 Preface 4
1.2 Data scientific problem 5
2. Practice 6
2.1 Dataset 6
3. Theory 6
3.1 Description 6
3.2 Analysis Gartner 6
3.3 V’s of Big Data 6
3.4 Deductive versus Inductive (Tuthill’s Wisdom Pyramid) 6
3.5 Push Left principal 6
3.6 Flexibility, MSE, Bias & Variance and trade off 6
4. Results 6
5. Appendix 6
4.1 Appendix I – Bibliography 6
⦁
⦁ Introduction
⦁ Preface
This paper will give a brief description of the company where I am working for and the general context of the data scientific problem I want to address. The second chapter of this paper will show the dataset I have used and give more insight on its relevance. The theory will describe the important touch points of each theory we have treated in our class. Once practice and theory have come together the results of the predictive model I have been trying to create will be discussed and outcomes of the model will be presented and concluded.
Before we go ahead, I wanted to point out to figure 1. This is a little roadmap on machine learning for defining a data scientific problem. Within this paper I will use these steps in order to decide what kind of problem my organization is facing.
Figure 1: Defining a Data Science problem. source: www.towardsdatascience.com
For my case I will be using data from my company. This organization is a multinational mobility provider and helps customers in mobility solutions. Innovation is undoubtedly its main point to gain and remain customer satisfaction. The company its thinking perspective goes from client to process and not the other way around. Fleet growth will always maintain an important aspect of its strategic perspectives. Therefore, I as a controller want to see if I can contribute to sales growth by using data science in an innovative matter.
⦁ Data scientific problem
⦁ Practice
2.1 Dataset
⦁ Theory
3.1 Description
3.2 Analysis Gartner
3.3 V’s of Big Data
3.4 Deductive versus Inductive (Tuthill’s Wisdom Pyramid)
3.5 Push Left principal
3.6 Flexibility, MSE, Bias & Variance and trade off
⦁ Results
⦁ Appendix
4.1 Appendix I – Bibliography
Comments from Customer
Can you please check whether you have these type of writers who can actually do a data science assignment and have acces to R or Python to create data sets and analysis. Access to car leasing company data is also mandatory.