Reference no: EM133697787

Introduction to Business Analytics

Assessment - Data Management, Analysis and Visualisation Project

Your Task

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.

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.

Assessment Task

Part A: Data Management

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 breakfast cereal. Suppose that you are an Analytics team for a sport and dieting company. You have been given data on the nutritional components (e.g. sugar, fat, protein...) of common breakfast cereals and a rating. You wish to determine which cereals are best for diabetics and those on special diets.

Data checking: Upload the data into Excel for an initial check. The file is a csv (txt) file. Check for missing data and errors.
You will notice some negative values which can be modified by looking up the components on the internet. If you can't find any information, use an approximate based on a similar product.
Sort the ratings from largest to smallest to get an idea of general customer approval of the cereals.
Save the file as an excel file for uploading into Power BI or Tableau.

Data Dictionary: Open the fields file that you have been given. From the information given, create a simple data dictionary for the file which outlines the name (top row) and data type in each of the remaining columns. Explain how the results can 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

Forming questions and visualising: Create four sub-questions and visualisations for each of them to show different nutrition-based aspects of the products. For example, which manufacturer produces products which contain the least amount of sugar? What would suit those on a high protein diet? Explain which visualization you think is the most effective in addressing the business question above? Why?

Filtering: With reference to two visuals, filter out some products at the extreme end. For example, cereals with at least 4 gm of protein or those with less than 3 grams of sugar or more than 3 grams of fat.

Summary statistics: Find the average vitamin (percentage of daily recommended dose) per manufacturer and summary stats (by switching from sum to average or median) for two other variables.
Sorting: Having sorted the ratings, arrive at a conclusion about what customers prefer to eat.

Summary and Recommendation: Summarise all of your findings and recommend which products should be promoted as being the least harmful for diabetics and others with special needs. Justify your answers with reference to the data analysis you have performed in the previous sections.