Project 00 (Problem Set 4): Mini Project

The objectives of the project are to:

Prompt

You have been tasked as analysts to investigate trends in sales data from three branches spanning 2017 through 2019. The decision-maker wants to leverage data insights to inform better business decisions but has not provided specific direction.

Your role is to:

  1. Conduct exploratory data analysis (EDA) to understand the dataset.
  2. Identify a meaningful insight worth sharing with management.
  3. Develop a compelling data story that effectively communicates your findings to the audience.

Once you find an insight, develop your data story.

R: Data Processing

Link to the description of the supermarket sales data available in the Supermarket Sales Data Overview.

Using R, complete the following steps:

  1. Combine Datasets. You are given sales data in three separate files (one for each year). Use R to append those datasets into a single dataset suitable for analysis and output it as a CSV file for Tableau.

  2. Handle Missing Data. There was a problem integrating the E-wallet payment system data with the rest of the dataset. The gross_income and gross_margin_percentage values are missing for transactions with E-wallet payments. Use other information in the dataset to fill in the missing values (labeled as β€œNA”) by calculating these fields. You can check your work by comparing your calculated values with those present in the dataset.

  3. Export the Dataset. Use R to write a csv file that your can read into Tableau.

Tableau: Data Visualization

Using Tableau, create at least three visualizations to support your data story. The visualizations can be static or interactive but should adhere to the guidelines for better data visualizations.

Visualization Requirements:

  • Each visualization should highlight a specific aspect of your analysis.
  • Be clear but informative while supporting your narrative effectively.

Google Sites: Webpage Report

Present your analysis as a comprehensive webpage report. The webpage should:

  1. Narrative: Include a written narrative of 500 to 750 words that explains your analysis and insights. Examples of questions you might ask the data are:
  • What are the sales trends over time? Are the patterns stable across branches/years?
  • What products generate the most sales? Which products yield the highest gross income? Does this vary by location?
  • How is customer satisfaction trending? Does this vary by location or product?

  1. Visualizations: Embed Tableau visualizations to support your narrative. Be sure that they support a narrative consistent with the questions you are asking and answering.

  2. Data Story Elements: The webpage should contain these elements:

  • Question or compelling hook: What are you investigating?
  • Characters and setting: Context of the sales data and branches.
  • Preliminaries: Important observations or trends leading to your insight.
  • Answer or insight: What is your main finding?
  • Next steps: What can the manager/decision-maker do with this information? What recommendations do you have for further analysis?
  • Limitations of analysis: What are the shortcomings of your analysis? How might you alter your data collection processes to revisit your question in the future?

Remember: This report is being written for a management team, so be sure to write the report with this audience in mind.

How to Submit

You should create a new webpage on your Google site titled Unit 0 Mini Project. This webpage should include a write up of your analysis including a brief description of any data processing steps. Generate a log file from your R code and submit that to Canvas. Submit the link to your Google site webpage in Canvas.

  1. Create a Webpage:
  • Title your webpage Unit 0 Mini Project.
  • Include the following:
    • A write-up of your analysis with a brief description of the data processing steps.
    • Embedded Tableau visualizations.
    • Your narrative (500–750 words).
  1. Generate a Log File:
  • Use the sink() command in R to create a log file that demonstrates your script ran successfully.
  1. Submit via Canvas:
  • Submit the link to your Google Site webpage in Canvas.
  • Upload your R log file as a separate submission.