Faang Sql Queries Part - 2

SQL QUERIES ASKED IN FAANG PART - 2

What you'll learn

SOLVE SQL QUERIES

FAANG SQL

SQL QUERIES ASKED IN PRODUCT BASED

HOW TO SOLVE SQL QUERIES STEP BY STEP

Requirements

Basic SQL Knowledge

Description

Solving SQL queries for FAANG (Facebook, Amazon, Apple, Netflix, Google) interviews requires a solid understanding of SQL fundamentals, along with the ability to approach problems efficiently. Here's a step-by-step guide on how to tackle FAANG SQL queries:1. Understand the Problem ClearlyRead the problem statement carefully: Understand what data is required and what results need to be produced.Look for key elements: Tables, columns, conditions, and any grouping/aggregation that might be necessary.Clarify edge cases: If the problem is ambiguous, ask questions to clarify details (e.g., handling NULLs, ties in ranking, etc.).2. Identify the Relevant Tables and ColumnsDetermine the main table: The one from which you’ll mostly pull data.Look at any relationships: Identify any JOINs between multiple tables if needed.Check for required columns: Know exactly which columns you’ll need for your SELECT statement.3. Choose the Right SQL ClausesSELECT: Specify which columns you need.FROM: Define the tables you are querying.WHERE: Add filters based on the conditions specified in the problem.JOIN: Use if you need to combine data from multiple tables.GROUP BY: When aggregating data, group by the relevant columns.HAVING: Use to filter grouped results (applies after aggregation).ORDER BY: Sort the results if needed.LIMIT: To restrict the number of rows returned (useful for ranking, top-N queries, etc.).4. Write the Query in StepsStart simple: Begin with a basic query that selects all the necessary columns from the relevant table(s).Apply filters: Add the WHERE clause to narrow down the dataset.Add aggregation (if required): Use COUNT, SUM, AVG, etc., along with GROUP BY.Optimize: If the query is too slow or complex, look for optimization opportunities (e.g., using indexes, eliminating unnecessary JOINs, or using subqueries).5. Handle Advanced ConceptsSubqueries: For complex filtering or when the result depends on a calculation based on other records.Window Functions: Useful for ranking, calculating running totals, moving averages, etc. Functions like ROW_NUMBER(), RANK(), and OVER() are frequently used in FAANG interviews.Common Table Expressions (CTEs): Used to simplify complex queries and improve readability.Joins: Be familiar with different types of joins (INNER, LEFT, RIGHT, FULL OUTER) and when to use them.Self Joins: Use when you need to join a table with itself (e.g., employee-manager relationships).6. Test with Sample DataBefore finalizing your query, check how it behaves with sample data, and test for edge cases.Be mindful of NULL values, duplicates, and large datasets.7. Explain Your Thought ProcessDuring an interview, explain your approach clearly. Discuss why you chose specific SQL constructs, like joins, groupings, and aggregations.If necessary, walk through the problem-solving steps and any trade-offs you made.

Overview

Section 1: SQL QUERIES ASKED IN FAANG - PRODUCT BASED COMPANIES

Lecture 1 1_Pharmacy Analytics (Part 3) [CVS Health SQL Interview Question]

Lecture 2 2_Pharmacy Analytics (Part 4) [CVS Health SQL Interview Question]

Lecture 3 3_Y-on-Y Growth Rate [Wayfair SQL Interview Question]

Lecture 4 4_Ad Campaign ROAS [Google SQL Interview Question

Lecture 5 5_Trade In Payouts [Apple SQL Interview Question]

Lecture 6 6_Cumulative Purchases by Product Type [Amazon SQL Interview Question

Lecture 7 7_Repeat Purchases on Multiple Days [Stitch Fix SQL Interview Question]

Lecture 8 8_Subject Matter Experts [Accenture SQL Interview Question]

Lecture 9 9_User Session Activity [Twitter SQL Interview Question]

Lecture 10 10_ApplePay Volume

SQL Professionals, Data Analysts, Data Engineers