Describe the summary statistics for variables

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Reference no: EM133763319 , Length: word count:1000

Introduction to Business Analytics

Assessment - Data Management, Analysis and Visualisation Project

Assessment Description
In groups of 4 to 5 class members (no more than 5 members) 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.

All students 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.

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

Form groups of 4-5 before class
Business Question: Based on the data set provided, which is best food to feed to a baby?
Data: The data files (data and fields) will be provided by your lecturer at the commencement of the class.
Software: Your team's choice of Power BI or Tableau

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)

Assessment Overview

Part A: Data Management (200 words)
50 Minutes
Instructions:

The data file and fields file will be provided by your lecturer at the commencement of the class. The data relates to nutrition of a range of food. Suppose that you are an Analytics team for a nutrition company. You have been given data on the nutritional components (e.g. sugar, fat, protein etc...) of various foods. You wish to determine which is best food to feed to a baby. The definition of "best" is for your group to explain and analyse.
Data Checking: Upload the data into Excel for an initial check. The file is a csv (txt) file. Check for missing data and errors.

State the number of data records you have in the sample
You may notice some negative values which can be modified using an approximate based on a similar product and state your changes
Provide any assumptions, changes and issues presented in the data that may impact your analysis

Sort the ratings from largest to smallest to get an idea of 3-4 of the key variables you have identified in your analysis and provide an overview of the range of nutrient values

Save the file as an excel file for uploading into Power BI or Tableau.

Data Dictionary: View the fields file that you have been provided. From the information given, create a thorough data dictionary for the file which outlines all aspects of the data. Explain how this could be applied to data succession management.

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?

Part B: Data Analysis and Recommendation ( 800 words)

Forming questions and visualising:

Create at least four sub-questions and visualisations. For each of them to show different nutrition-based aspects of the products and produce an insight describing what is being shown.
For example, which manufacturer produces products which contain the least amount of sugar?
Explain which visualization you think is the most effective in addressing the business question above? Why?

Filtering:

With reference to two visuals produced in Part B1, filter out some products at the extreme end and produce an insight describing what is being shown.
For example, food with at low levels of protein or those with high level of sugar
Summary statistics:

Describe the summary statistics for 3 variables and produce an insight describing what is being shown.
For example, find the average vitamin per manufacturer and summary stats (by switching from sum to average or median) for two other variables.
Sorting:
Having sorted the values for some of the nutriants, comment on your findings

Summary and Recommendation:

Summarise your analysis and recommend which products are the best based on your criteria. Justify your answers with clear reference to the data analysis you have performed in the previous sections.

Reference no: EM133763319

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