SQL Interview Practice Questions

Explore a sql case study on manager job postings, labeling each job as new, active, or reactivated using lag dates and a 180 days rule, with window functions and counts.

Analyze survey data with SQL to count total surveys, responders, and non-responders; compute per-user stats and day differences using case statements and lag functions.

Compute the average salary by department, left outer join the result with the department salary table, and filter employees whose salary exceeds their department's average.

Learn how to compute each account's balance as of a given input date using a window function to pick the latest transaction before that date.

Join the sales and product reference tables on product_id, sum revenue per product, and use dense_rank partitioned by category to identify the top three products.

Apply window functions to each customer to retrieve the highest total paid and the second lowest paid total using partition by customer id, max, and row_number with an inner join.

Show how to identify customers with three consecutive status_id of 19 using a case statement and lead function, partitioned by customer_id and ordered by origination_date, outputting the IDs and dates.

Construct a SQL query to find employees who earn more than their managers by joining manager_id with a subquery of managers' salaries, then filter where employee salary exceeds manager salary.

Identify customers who never ordered by left joining the customers table with the orders table and filtering where order IDs are null, returning Nancy and Sarah.

Identify dates where the temperature exceeds the previous day using a lag-based query on a table of id, date, and temperature, and filter to current greater than previous.

Identify the maximum salary, then select salaries below it, order by salary descending, and pick the top result to obtain the second highest salary.

Examine a user login data set to determine each user's first login date by computing the minimum login date per user ID, then sort by that date.

Compute monthly new and repeated users in SQL by identifying each user's first login date, joining tables, counting distinct users per month, and calculating running totals and proportions.

Compute total logins by year, month, and day, then apply a window function to compute a running sum across days.

Identify active and inactive users by calculating days since their recent login with a max window function and date diff, using a 15-day threshold. Group by status to show counts.

Learn to identify the top three users per location by total logins using window functions, partitioning by geography and ordering by login counts to filter the top results.

Practice sql interview prep by writing complete, workable sql first; explain your approach if needed, and study joins, subqueries, window functions, and aggregation with LeetCode and HackerRank.

Learn to build and evaluate a regression machine learning model using ChatGPT in Python notebook, covering data loading, cleaning, visualization, feature engineering, model selection with XGBoost, training, and evaluation.