Data Challenges
Scenario:
Congratulations! You’ve just been hired as a Junior Data Analyst at Marcy Market, a growing community-based grocery chain with locations in Brooklyn, the Bronx, Queens, and Manhattan. Your mission? Help the leadership team understand customer behavior, regional sales performance, and product-level trends using a dataset from 2024.
Marcy Market is deeply rooted in the community and proud of its values. Your manager, Stephanie Smith (a former Marcy alum), started as a store associate 15 years ago and worked his way up to become CEO. Now, Stephanie wants to use data to guide business decisions that better serve customers and build the company’s future, and he’s counting on your help.
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PART ONE: ORGANIZING & ANALYZING DATA
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PART 1 TASK 1: GETTING TO KNOW THE DATA
You’ll explore a real dataset to describe what types of information are included, such as borough, product category, sales, and units sold, and answer observation-based questions that help you get oriented to the structure, timeframes, and early patterns in the data, before diving into analysis.
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PART 1 TASK 2: INTERPRETING TRENDS USING PIVOT TABLES
You’ll review two pre-built pivot tables (Total Sales and Total Units Sold by borough and month) and answer questions about seasonal trends, borough-level differences, and what patterns in sales vs. units sold might suggest about pricing, product strategy, and key follow-up questions a store manager should explore.
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PART 1 TASK 3: CREATING PIVOT TABLES & GENERATING BUSINESS INSIGHTS
You’ll create two pivot tables (Total Sales by month/borough/category and Total Units Sold by month/category), use them to model a Produce sales drop and estimate Bakery growth, and then answer questions that help you interpret momentum across categories, compare sales vs. volume by borough, and connect trends to business strategy.
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PART 2: PRESENTATION
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PART 3: WRITTEN REFLECTION