SQL Interview Scenarios for ETL & BI Developers Part 1

Convert rows to columns in SQL by pivoting with case statements or aggregation, using a practical interview scenario to transform subject rows into maths, English, and science columns.

This lecture shows how to turn columns into rows from a data table, identify the columns to convert, apply aggregation where needed, and verify the result via a sorted order.

Apply SQL to multiply two columns and expand rows, using analytic functions to generate repeated values for ETL and BI development scenarios.

Learn to concatenate the second and third columns into a string separated by a pipe, using a within group list aggregate and substring to handle spaces and trailing separators.

Demonstrates repeating a column value across rows with a level-based query, using connect by level, the max of the column, and a sequence to generate multiple output rows.

Convert a single column into multiple columns by using an analytic function with partition and rank, then pivot rows to columns with a case when expression.

Generate the first day of every month and the last day of every month for a 12-month period using SQL date functions and the level function.

Eradicate duplicate values by ranking city names through ascii-based comparisons and case when logic to produce a two-column, three-row result based on travel distance.

Learn to display current quarter data from a given date by identifying the quarter's start and end dates and returning a complete current-quarter report using date calculations.

Learn how to display the previous quarter data from a given date in SQL, using quarter truncation and date arithmetic to compute the start and end dates.

Compute previous and next month start and end dates from a date column using add months and date functions, including the last Thursday and last day of the next month.

Learn how to repeat rows based on a quantity column to expand output, using a level-based approach and comparing ANSI 92 join methods with older syntax.

Learn how to use the merge statement to upsert data in ETL workflows, performing insert, update, and delete in a single operation based on matching conditions between source and target.

Demonstrate calculating a cumulative sum with a window function over an ordered value column, using over and order by to accumulate row totals.

Use a self join on the employees table to count how many staff report to each manager, producing employee and manager names with a report count.

Split a word into multiple rows by character using by level and substring in SQL, demonstrated on India to generate one row per character for ETL and BI interviews.

Learn to convert columns to rows in SQL by applying a simple union all approach and a scalable generic method, handling scenarios with hundreds of columns.

Explore the difference between rank and dense_rank in SQL using window functions to rank salaries within departments, handle ties, and generate sorted outputs for ETL and BI workflows.

Learn to count row occurrences and display the result for each value in a single column using join-based methods and analytic window functions in SQL for ETL and BI contexts.

Determine start and end dates of the previous and next quarters using the current date, constructing a SQL query with first and last day calculations for quarterly boundaries.

Explore generating cricket match schedules from two-column input with SQL lead and lag window functions, creating dynamic pairings like India versus Pakistan, Pakistan versus Australia, and Australia versus India.

Generate all uppercase and lowercase alphabets in SQL using ASCII values and a level-based analytic function, demonstrating how to produce A–Z and a–z in query results.

Convert read, write, and execute flags to binary values using SQL case statements; build and populate a table, apply the logic, and display the resulting four-column output.

Learn to convert columns to rows using an unpivot technique to transform a single-row input into multiple rows and display filenames.