Starting with a classic

When you're just getting started with data analysis, choosing the right dataset can feel overwhelming. Instead of spending hours searching for the perfect one, why not begin with a classic? The Superstore dataset is included by default in Tableau Public and Desktop is a go-to for a reason. It's clean, comprehensive, and familiar to most analysts.

The key is to focus on one specific angle and build a meaningful story from there. For my first post, I decided to dive into the Profit aspect of the Superstore data. I created an interactive Tableau dashboard to explore trends, patterns, and key takeaways.

Keep reading to see what I discovered—and let’s analyze some data together!

Superstore - Profit (Tableau Public link)

Moving forward, I’ll highlight four key insights I uncovered while analyzing this dataset—and use them to help tell a clear, data-driven story.

1. More Profitable during q4

While Superstore is overall a profitable business, Q4 clearly stands out as its strongest quarter, consistently generating between $37K and $43K in profit.
Copiers lead the way in Q4, bringing in $32K in profit, followed closely by Phones, which contributed $23K.
When it comes to individual products, the Canon Class 2200 stands out as a top performer, generating an impressive $17K in profit during this period.

2. Our 3 leading states

California - $76k
New York - $74k
Washington - $33k

The data shows that Binders ($27K), Copiers ($23K), and Accessories ($21K) are the top-performing sub-categories in terms of profit across our three highest-earning states. Even more impressive—none of the sub-categories are operating at a loss in these states, highlighting consistent profitability across the board.

3. Our 3 Lagging states

Texas -$25k
Ohio -$17k
Pennsylvania -$15k

The data shows that Machines ($17K), Tables ($8K), and Bookcases ($7K) are the bottom-performing sub-categories in terms of loss across our lowest-earning states. From this story, management should discontinue these types in these specific states to become more profitable!

4. Taking from Superstore Profit

Tables -$18k
Bookcases -$3k
Supplies -$1k

After analyzing the data for the bottom three product types, it’s clear that they generated no profit at all between 2018 and 2021. To improve overall profitability, Superstore should strongly consider discontinuing these underperforming categories from their inventory.

Conclusion

Analyzing the Superstore dataset through the lens of profit revealed some valuable insights into seasonal trends, top-performing categories, and areas of underperformance. It’s clear that Q4 is a key driver of success, and certain products like the Canon Class 2200 play a major role in boosting profitability. Identifying what works and what doesn’t, is essential for making smarter business decisions. This exercise demonstrates how even a well-known dataset can uncover meaningful stories when approached with focus and curiosity. Stay tuned for future posts where I’ll continue exploring data and sharing insights through visual storytelling.

— Adam Davidson

Superstore Dataset