Reference no: EM131026866 , Length: word count:1000

Task 1a: Assignment requires that you research and critically evaluate literature surrounding the problem of effectively assessing loan applications for credit worthiness. Credit worthiness assessment reduces risks associated with lending by determining which potential low applications are considered to be good, or alternatively a poor, credit risk and should on that basis be approved or rejected. Good risk management of loan applications can significantly improve the bottom line of financial institutions such as banks, building societies and credit unions. This research will inform your assessment of the key variables in credit data set which is provided for Assignment 2.

Task 1b: Using Rapid Miner conduct an exploratory data analysis of the creditdata.csv to identify five variables and build a decision tree model for predicting the credit score of customers and present and discuss the results of your exploratory data analysis and decision tree analysis.

Task 2 a) Discuss the possible approaches could be used for designing a data warehouse architecture using Kimball or Inmon's methodology and provide a high level logical design of a data warehouse in a diagram.

Task 2 b) Discuss how your high level warehouse architecture design in part A could incorporate the capture, processing, storage and presentation of big data. Your answer here should focus on providing explanation of a revised high level diagrammatic representation of the logical design of your data warehouse that show how big data analytics would be incorporate/integrated in the design.

Task 3 a) Create a report and accompanying graph using Tableau that shows a trend analysis for sales by Product Category over the years 2009 to 2012 and comment on key trends and patterns apparent in this report.

Task 3 b) Create a report and accompanying graph using Tableau that shows for each Product Category Average Profit and Total Sales for each month over the years 2009 to 2012 and comment on key trends and patterns apparent in this report.

Task 3 c) Create a geographical map presentation using Tableau that shows graphically the relative size by City within each state, Product Sales for year 2010 and comment on key trends and patterns in this report.

Task 3 d) Create a report and accompanying graph using Tableau that shows for Product Sub Categories that are technology based Unit Prices, Sales and Profit for each month over the years 2009 to 2012 and comment on key trends and patterns in this report.

Task 1 Exploratory Data Analysis and Decision Tree Analysis

a) Assignment 2 requires that you research and critically evaluate literature surrounding the problem of effectively assessing loan applications for credit worthiness. Credit worthiness assessment reduces the risks associated with lending by determining which potential loan applications are considered to be good, or alternatively a poor, credit risk and should on that basis be approved or rejected. Good risk management of loan applications can significantly improve the bottom line of financial institutions such as banks, building societies and credit unions. This research will inform your assessment and identification of the key variables in the credit data set which is provided for Assignment 2. Note you should also refer to the data dictionary provided in Appendix A of this document and with the creditdata.csv file as this document defines each of the variables and their range of values. (About 250 words).

b) Using RapidMiner Studio data mining tool conduct an exploratory analysis of the creditdata.csv data set on the Assignment 2 folder on course study desk which is provided on the on course study desk to identify what you consider to be top five key variables which contribute to determining whether a potential loan applicant is a good credit risk or a bad credit risk. Note you should also refer to the data dictionary provided in Appendix A of this document and with the creditdata.csv file as this document defines each of the variables and their range of values.

Then using RapidMiner Studio data mining tool build a simple predictive model of Credit risk using a reduced creditdata.csv data set using a DecisionTree.

Discuss each of your five top variables in about 50 words in terms of the results of your exploratory data analysis and discuss the results of your decision tree analysis drawing on the key outputs from RapidMiner Studio data mining tool and the relevant supporting literature on credit assessment and relevant supporting literature on the interpretation of decision trees. Your discussion should also include appropriate statistical analysis results such as graphs and results tables from conducting an exploratory data analysis in the RapidMiner data mining tool with some supporting references on predictive model building and interpretation using Decision Trees in data mining (about 250 words).

Task 3 Sales Reports using Tableau Desktop (Worth 25 Marks)(500words)

Task 3 Sales Reports using Tableau Desktop consists of the following sub tasks

With the following Excel file SalesSuperstore.xlsx provided on the course study desk Assignment 2 Folder link and using Tableau Desktop produce the four following reports with appropriate accompanying graphs based on a Tableau workbook sheet view for each. Briefly comment on each report in about 125 words in terms of what trends and patterns are apparent in each report.

The SalesSuperstore.xlsx file contains the following dimensions and information:

1. Customer Name, Customer Segment

2 . Location - Region, State, City, Zipcode

3. Product Category, Sub Category, Product Name, Product Container, Unit Price

4. Order Information

5 . Shipping Information

6. Sales Information

7. Profit

a) Create a report and accompanying graph using Tableau that shows a trend analysis for sales by Product Category over the years 2009 to 2012 and comment on key trends and patterns apparent in this report (About 125 words)

b) Create a report and accompanying graph using Tableau that shows for each Product Category Average Profit and Total Sales for each month over the years 2009 to 2012 and comment on key trends and patterns apparent in this report (About 125 words)

c) Create a geographical map presentation using Tableau that shows graphically the relative size by City within each state, Product Sales for year 2010 and comment on key trends and patterns in this report (About 125 words)

d) Create a report and accompanying graph using Tableau that shows for Product Sub Categories that are technology based Unit Prices, Sales and Profit for each month over the years 2009 to 2012 and comment on key trends and patterns in this report (About 125 words)

Your assignment 2 report must be structured in report format as follows:

Cover page for assignment 2 report
1. Title Page
2. Table of Contents
3. Body of report - main sections and subsections for assignment 2 task and sub tasks so
3.1 Task 1 will be a main heading with appropriate sub headings etc....for each sub task etc..

3.2 Task 2 ...

3.3 Task 3 ....
4. List of References
5. List of Appendices

You need to submit two files when you submit Assignment 2

1. Your Assignment 2 Report for Tasks 1, 2 and 3 in Word document format with the extension .docx
2. Your Assignment 2 Task 3 as a Tableau packaged workbook with the extension .twbx

Appendix A Data Dictionary and Description of the creditdata.csv data set.

1.  Title: German Credit data - creditdata.csv

2.  Number of Instances:  1000

3.  Number of Attributes:  22 (8 numerical, 14 categorical)

4.    Table with Attribute description for creditdata.csv

Attribute Name		Type of Attribute	Range of attribute
1.	Custno	Customer Id	Custno1 to Custno1000
2.	Checking	Status of existing checking account (qualitative)	A: <= 0 DM
			B: <= 200 DM
			C: >= 200 DM / Salary assignments for one year
			D: No checking account
3.	duration	Duration in months of loan (numeric)
4.	history	Credit history (qualitative)	A: no credits taken/ all credits paid back duly
			B: all credits at this bank paid back duly
			C: existing credits paid back duly till now
			D: delay in paying off in the past
			E: critical account/other credits existing (not at this bank)
5.	purpose	Purpose of proposed loan (qualitative)	A: car
			B: car (used)
			C: furniture/equipment
			D: radio/television
			E: domestic appliances
			F: repairs
			G: education
			H: (vacation)
			I: retraining
			J: business
			K: others
6.	amount	Credit amount (numeric)

7.	savings	Savings account/bonds (in German currency)	A: < 100 DM
		(qualitative)	B: 100 <= ... < 500 DM
			C:  500 <= ... < 1000 DM
			D:  >= 1000 DM
			E:  unknown/ no savings account
8.	employed	Present employment since (qualitative)	A: unemployed
			B: < 1 year
			C: 1	<= ... < 4 years
			D: 4	<= ... < 7 years
			E: >= 7 years
9.	instalp	Instalment rate as percentage of disposal income
		(numeric)
10. marital		Personal status and sex (qualitative)	A: male: divorced/separated
			B: female : divorced/separated/married
			C: male		: single
			D: male		: married/widowed
			E: female : single
11. coapp		Other debtors / guarantors (qualitative)	A: none
			B: co-applicant
			C: guarantor
12. resident		Present residence since (numeric) in years
13. property		Property (qualitative)	A: real estate
			B: if not A: building society savings agreement/life
			insurance
			C: if not A/B: car or other, not in attribute 6
			D: unknown / no property
14. age		Age in years (numeric)
15. other		Other instalment plans	A: bank
			B: stores
			C: none

16. housing	Housing (qualitative)	A: rent
		B: own
		C : for free
17. excred	Number of existing credits at this bank (numeric)
18. job	Job (qualitative)	A: unemployed/ unskilled  - non-resident
		B: unskilled - resident
		C: skilled employee / official
		D: management/ self-employed/
		highly qualified employee/ officer
19. depends	Number of people being liable to provide
	maintenance for (numeric)
20. telephone	Telephone	A: none
		B: yes, registered under the customers name
21. foreign	Foreign worker (qualitative)	A: yes
		B: no
22. credit_rating	Credit rating (qualitative)	Good
		Bad

Attachment:- creditdata.rar