Experience: 1–3 Years
CTC: 22 LPA+
These are few questions I have compiled that I have encountered in my data analyst interview experience at Walmart.
1. Find the second-highest salary per department but exclude departments where fewer than 3 employees exist.
2. For each user, calculate the 7-day moving average of transactions, considering transaction dates with gaps.
3. Given two tables: projects (project_id, budget), employees (employee_id, project_id), find the project with the highest “budget per unique role.” Assume an employee_roles table exists.
4. Identify users who had a transaction amount 2x higher than their average transaction amount in the past 30 days.
5. Compare Import vs Direct Query modes in the context of handling real-time data from a distributed warehouse system with high latency.
6. What is the difference between a visual-level filter, page-level filter, and a report-level filter? Provide an example where improper use leads to misleading analytics.
7. Design a Power BI dashboard with Row-Level Security (RLS) where a user might belong to multiple departments. How would you implement dynamic RLS using DAX?
8. Using pandas, merge three datasets (sales, promotions, inventory). Return top 5 products with the highest uplift in sales during a valid promotion window.
9. Implement a custom function in pandas that bins continuous numerical data into deciles and labels outliers based on the IQR method. Return a summary table. |
10. Compare and contrast defaultdict, Counter, and regular dictionaries in Python. When would you use each for analyzing customer purchase patterns?
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Hi, I’m Mathilde Lacombe — a lifestyle and beauty blogger based in New York City. I have been writing about beauty, skincare, fashion, health, and women’s everyday life for nearly eight years. I hold a Master’s degree in Arts & Humanities from Pace University, New York, which shaped the way I research, analyse, and write about every topic I cover here.
I started this blog because I wanted a space for honest, well-researched content, not recycled advice or paid promotions dressed up as genuine recommendations. Everything I publish starts with research and ends with a real opinion.
When I am not writing, you will find me exploring New York City, obsessing over skincare ingredients, or spending time with my pets. This blog is my creative home and I am glad you found it.
