You’ve just started a new job as a data analyst. You’re working for a midsized pharmacy chain with 38 stores in the American Southwest. Your supervisor shares a new data analysis project with you.
She explains that the pharmacy is considering discontinuing a bubble bath product called Splashtastic. Your supervisor wants you to analyze sales data and determine what percentage of each store’s total daily sales come from that product. Then, you’ll present your findings to leadership.
You know that it’s important to follow each step of the data analysis process: ask, prepare, process, analyze, share, and act. So, you begin by defining the problem and making sure you fully understand stakeholder expectations.
One of the questions you ask is where to find the dataset you’ll be working with. Your supervisor explains that the company database has all the information you need.
Next, you continue to the prepare step. You access the database and write a query to retrieve data about Splashtastic. You notice that there are only 38 rows of data, representing the company’s 38 stores. In addition, your dataset contains five columns: Store Number, Average Daily Customers, Average Daily Splashtastic Sales (Units), Average Daily Splashtastic Sales (Dollars), and Average Total Daily Sales (All Products).
Considering the size of your dataset, what’s the best way to proceed with the process and analyze steps?
Correct
Spreadsheets work well for processing and analyzing a small dataset, such as the one you’re using.
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