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Can you solve this real Amazon SQL interview question, about finding the highest-grossing items in each category? Problem Statement, Input Data, & Hints below 👇👇

𝐑𝐞𝐚𝐥 𝐀𝐦𝐚𝐳𝐨𝐧 𝐒𝐐𝐋 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧: Given a reviews table, write a SQL query to retrieve the average star rating for each product, grouped by month. Can you solve it??? Full Problem Statement, Input Data, & Hints Below 👇👇

Solve this LinkedIn SQL Interview Question together! Given a table containing job postings from various companies on the LinkedIn platform, write a query to retrieve the count of companies that have posted duplicate job listings. Input Data & Our Solution 🧵👇

The 5 most common aggregate functions used in SQL interviews are: AVG() - Returns the average value COUNT() - Returns the number of rows MAX() - Returns the largest value MIN() - Returns the smallest value SUM() - Returns the sum Let's practice these on a JP Morgan dataset:

Can you solve this real Microsoft SQL interview question: “Which Azure customer buys at least 1 Azure product from each product category?” You're given a customer_contracts table & a table of Azure products.

Can you solve this Google SQL Interview Question??? Be warned, it's kinda tricky...

SQL Interviews LOVE to test you on Window Functions. Here’s the 7 most popular window functions & some real SQL interview questions to practice these commands 👇

Microsoft SQL Interview Question: Write a query to identify the top 2 Power Users who sent the highest number of messages on Microsoft Teams in August 2022. Display the IDs of these 2 users along with the total number of messages they sent.

Snapchat pays Data Scientists $250k+ Can you solve a real Snap SQL Interview question?

Forget about the "Science" in "Data Science" when starting out. Wise words from Daliana Liu (Daliana Liu)

Google's results for "SQL Interview Questions" are SUPER SHITTY. Hiring a plumber? You'd ask 'How to unclog this💩?' not 'What is a toilet🚽?' Similarly, data interviews don't ask 'What's SQL?'. They craft ask you to write SQL queries to answer realistic business questions.

People underestimate the “Data” part of Data Science. Most of the work in real-world Data Science is focussed on: • acquiring the data • understanding the data • cleaning the data Not building fancy predictive models. Plan accordingly.

On this day, nine years ago, Harambe was fatally shot at the Cincinnati Zoo. We built DataLemur 🐵 | Ace the SQL Interview in honor of his memory, and all the other Primates who love SQL. #RIP

If you’re starting out in Data Science/Analytics, don’t worry about probability, statistics, or Machine Learning. Start by learning SQL, then get get good at visualizing data in a tool like Excel or Tableau. At the start of your data journey, don't overcomplicate things!

When you remove an important “WHERE” from your SQL query 🙃

Data Science interviews cover WAY more than just SQL. You can expect technical questions on: •Probability & Statistics •Machine Learning •Coding (Pandas) •Product-Sense •A/B Testing To help you prep, here's a FREE 9-day Data Interview Crash Course: acethedatascienceinterview.com/crash-course

Can you solve this Amazon SQL interview question? Given a table of Amazon customers & their purchases, write a query to identify the top two highest-grossing products within each category in the year 2022. p.s. test your SQL query on DataLemur: datalemur.com/questions/sql-…

Your first attempt learning ML will suck. Your first attempt writing SQL will sick. Your first attempt at data-viz will suck. Your first attempt in anything will suck. But you can’t make your 10th, 50th, or 100th without making your first. So don’t worry, just do it!

6,000-Word SQL Interview Guide for Data Analysts & Data Scientists. It Covers: 🔹SQL Questions from FB, Amazon, etc. 🔹Must-Know SQL Commands 🔹6-Step Process to Solve Hard Questions 🔹Sites to Practice SQL Questions 🔹4 Take-Home SQL Challenges Link: datalemur.com/blog/sql-inter…

If you’re starting out in Data Science/Analytics, don’t worry about probability, statistics, or Machine Learning. Start by learning SQL, then get get good at visualizing data in a tool like Excel or Tableau. At the start of your data journey, don't overcomplicate things!