Page 1 Kaplan Business School Assessment Outline

Assessment 2 Information

Subject Code: DATA4000

Subject Name: Introduction to Business Analytics

Assessment Title: Data Management, Analysis and Visualisation Project

Assessment Type: Group Project

Word Count: 1000 Words + Visualisations (+/-10%)

Weighting: 30 %

Total Marks: 30

Submission: In class (In Online workshop)

Due Date: Week 10

Your Task

In groups of 4-5 you are to perform a number of data management, analysis and visualisation tasks using your BI (Business Intelligence) tool of choice. Consider the business question and data set below and complete Parts A and B below in a group in Week 10 class time. EVERY MEMBER of the group will need to have access to a laptop or a desktop computer in order to contribute to this task. Student will need to have downloaded and installed a BI tool of their choice. Online students will complete this task over online workshop and should have access to a BI tool on their machines.

Page 2 Kaplan Business School Assessment Outline

Assessment Description

Your group will be asked to address the business question below with reference to the data provided and software of your choice.

• Business Question: Based on the New York Times bestseller list 2011 – 2018, what types of books and which titles should be stocked by the owner of a bookstore?

• Data: The data file will be provided by your lecturer at the commencement of the class.

• Software: Your team’s choice of Power BI, Tableau or Tibco Spotfire

• This assessment covers learning outcomes 3 and 4

Assessment Instructions

Face-to-Face Students

• Form groups of 4-5 before class

• Each group needs to ensure they bring at least one laptop to the class in Week 10 and have access to a data visualisation software (free student license)

• Your lecturer will email the books data set to your groups at the start of class.

• Complete the assessment task below in groups: o You will have 1 hour to do Part A below (Data Management) as a group after

which you will have one group member upload to the assessment portal via TurnItIn o You will have 1.5 hours to do Part B below (Data Analysis and Recommendation)

as a group after which you will have one group member upload to the assessment portal via TurnItIn

• This task is open book

Online Students

• Form groups of 4-5 before class

• Each group needs to ensure they attend the online workshop in Week 10 and have access to a computer and data visualisation software (free student license)

• Your lecturer will email the books data set to your groups at the start of class.

• Complete the assessment task below in groups: o You will have 1 hour to do Part A below (Data Management) as a group after

which you will have one group member upload to the assessment portal via TurnItIn o You will have 1.5 hours to do Part B below (Data Analysis and Recommendation)

as a group after which you will have one group member upload to the assessment portal via TurnItIn

• This task is open book

Page 3 Kaplan Business School Assessment Outline

Assessment Task Part A: Data Management (10 marks, 200 words) – 1 hour Instructions:

1. The data file will be provided by your lecturer at the commencement of the class.

2. Pre-cleaning: Open the BI tool and load the file copy, however do not import columns “book_review_link”, “primary_isbn13”, “sunday_review_link” and “first_chapter_link”. Ensure that the format of the columns is correct (i.e. dates should be dates and numbers should be integers or real).

3. Currency conversion:

The price is shown in column G. The currency type for the price is shown in column Q. Before you carry out your analysis, all prices must be converted to a single currency and this value entered into ‘converted_price’ in column R. Undertake this conversion using the vlookup command in Excel. The currency pairs are as follows:

Your lecturer will advise you at the start of class which base currency to convert all prices to.

4. Data Dictionary: Write a simple data dictionary for the file which outlines the name (top row) and data type in each of the remaining columns. Explain how you constructed this dictionary and how it can be applied to data succession management.

5. Data Security: Explain how you will back up the data and keep it secure throughout the data

management process. What challenges are associated with this?

AUD EUR GBP USD

AUD 1 0.62 0.55 0.7

EUR 1.61 1 0.89 1.13

GBP 1.82 1.12 1 1.26

USD 1.43 0.88 0.79 1

How to use this table:

1 unit of the ROW currency is worth [X] units of the COLUMN currency.

E.g. 1 AUD is worth 0.55 GBP; 1 GBP is worth 1.82 AUD

ON

E O

F

TH

ES

E…

…IS WORTH [X] OF THESE…

Page 4 Kaplan Business School Assessment Outline

Part B: Data Analysis and Recommendation (20 marks, 800 words) – 1.5 hours

1. Visualising: Create three different visualisations to show the top ten best-selling books. One visual must address ‘age group’. Another visual must address ‘genre’. Which one is the most effective in addressing the business question above? Why?

2. Filtering: Filter out the best five authors for the total time period and provide visualisations showing each author and their books to see if they have had more than one book (the titles will appear) on the list and cumulatively the sum of weeks all books were on the list.

3. Summary statistics: Find the average number of weeks any book was on the bestseller list. How many weeks was the top selling book on the list and what was the title of the book? Provide any other summary statistics that you think will be useful (e.g. median, mode, range).

4. Sorting: Sort the data by year and determine which book was the best seller in each year. Make a list/chart of these best-selling book titles. Briefly explain your findings.

5. Quadrant analysis: Consider the data on two dimensions of your choice (e.g.: weeks vs

price) and analyse which books/authors/publishers perform the best on both dimensions. Discuss any patterns that emerge.

6. Recommendation: Briefly recommend to a bookstore owner which titles they should stock.

Justify you answer with reference to the data analysis you have performed.

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Important Study Information

Academic Integrity Policy KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy. What is academic integrity and misconduct? What are the penalties for academic misconduct? What are the late penalties? How can I appeal my grade? Click here for answers to these questions: http://www.kbs.edu.au/current-students/student-policies/.

Word Limits for Written Assessments Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded.

Study Assistance Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click here for this information.

Page 6 Kaplan Business School Assessment Outline

Assessment Marking Guide

Section Criteria NN (Fail) 0%-49%

P (Pass) 50%-64%

CR (Credit) 74%-65%

DN (Distinction) 75%-84%

HD (High Distinction) 85%-100%

Part A: Data Management (10 marks)

Construct a data dictionary by importing, cleaning and managing a data set and reflect on security issues associated with data storage

Failure to demonstrate skills in data handling, cleaning and management and failure to create a useful data dictionary. Incomplete consideration of issues associated with storing and sourcing large amounts of data

Basic data handling, cleaning and management and the creation of a minimal data dictionary. Articulation of some issues associated with storing and sourcing large amounts of data

Competent data handling, cleaning and management and the solid creation of a data dictionary. Clear evaluation of relevant issues associated with storing and sourcing large amounts of data

Efficient data handling, cleaning and management and the creation of a well-constructed data dictionary. Effective evaluation of relevant issues associated with storing and sourcing large amounts of data

Sophisticated level of data handling, cleaning and management and the creation of a comprehensive data dictionary. Comprehensive evaluation of complex issues associated with storing and sourcing large amounts of data

Part B: Data Analysis and Recommendation (20 marks)

Filter, sort and visualise data to extract key statistics from a data set and perform quadrant analysis using data visualisation software. Communicate a data-driven business recommendation based on data analysis

Failure to extract key statistics from data and to follow instructions Visualisations are not correct or relevant and no relevant recommendations are made

Basic analysis of data and limited summary of statistics conducted. Creation of partially accurate data visualisations which inform the business recommendations

Adequate analysis of data and summary of main statistics. Creation of mostly accurate data visualisations and brief business recommendations supported by this data

Effective analysis of data and solid articulation of main statistics. Creation of accurate data visualisations in line with instructions and informed business recommendations supported by data

Comprehensive analysis of data and thorough articulation of key statistics. Creation of highly relevant and accurate data visualisations in line with instructions which underlie the business recommendations made based on that data

Comments:

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Assignment Submission

One student from each group must upload their assessment to the portal via TurnItIn immediately at the end of class time.

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