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@sqlspecialist

Data Analytics

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PostedApr 2004/20/2025, 04:28 AM
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Amazon Data Analyst Interview Questions for 1-3 years of experience role :- A. SQL: 1. You have two tables: Employee and Department. - Employee Table Columns: Employee_id, Employee_Name, Department_id, Salary - Department Table Columns: Department_id, Department_Name, Location Write an SQL query to find the name of the employee with the highest salary in each location. 2. You have two tables: Orders and Customers. - Orders Table Columns: Order_id, Customer_id, Order_Date, Amount - Customers Table Columns: Customer_id, Customer_Name, Join_Date Write an SQL query to calculate the total order amount for each customer who joined in the current year. The output should contain Customer_Name and the total amount. B. Python: 1. Basic oral questions on NumPy (e.g., array creation, slicing, broadcasting) and Matplotlib (e.g., plot types, customization). 2. Basic oral questions on pandas (like: groupby, loc/iloc, merge & join, etc.) 2. Write the code in NumPy and Pandas to replicate the functionality of your answer to the second SQL question. C. Leadership or Situational Questions: (Based on the leadership principle of Bias for Action) - Describe a situation where you had to make a quick decision with limited information. How did you proceed, and what was the outcome? (Based on the leadership principle of Dive Deep) - Can you share an example of a project where you had to delve deeply into the data to uncover insights or solve a problem? What steps did you take, and what were the results? (Based on the leadership principle of Customer Obsession) - Tell us about a time when you went above and beyond to meet a customer's needs or expectations. How did you identify their requirements, and what actions did you take to deliver exceptional service? D. Excel: Questions on advanced functions like VLOOKUP, XLookup, SUMPRODUCT, INDIRECT, TEXT functions, SUMIFS, COUNTIFS, LOOKUPS, INDEX & MATCH, AVERAGEIFS. Plus, some basic questions on pivot tables, conditional formatting, data validation, and charts. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://t.me/DataSimplifier Like if it helps :)