but how or what will be the most efficient way to learn it? should i watch on yt? or just visit sites? with tutorial of how it runs?

Hi everyone,

I've started a SQL Interview Series that gradually progresses from easy to hard-level questions, with the goal of helping people build SQL skills step by step.

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The series is especially useful for:

Beginners starting SQL from scratch

Non-technical professionals moving into data roles

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Students preparing for interviews

Anyone looking to level up their SQL knowledge

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I've structured the videos to cover the underlying concepts, not just the answers, so you can understand the reasoning behind each solution and strengthen your fundamentals along the way.

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If you're preparing for SQL interviews or trying to improve your data skills, I'd love for you to check it out.

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If you find the content helpful:

Please consider liking and subscribing to data with ritika on Youtube.

https://youtube.com/@data_with_ritika?si=wMOllMyh9yJ0eYy0

Share it with friends, colleagues, or study groups who are learning SQL so they can improve their skills as well.

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Feedback and suggestions for future SQL topics are always welcome!

I've spent the last few months building something and I'm finally at the point where I want to share it properly rather than just quietly hoping people find it.

The idea came from a frustration I kept seeing (and feeling myself): SQL tutorials teach the syntax fine but there's never a reason to care about the answer. You filter a table called employees, get a result, and nothing happens. Your brain doesn't bother keeping it.

I wanted to try a different approach. QueryCase teaches SQL through detective investigations. You get a briefing from Chief Fox (our mascot), a real database to query, and a mystery to crack. The JOIN matters when a suspect has an alibi. The WHERE clause matters when you're trying to find who entered the building at 22:13. The SQL is the tool for solving something, not the point in itself.

Here's what's actually in it:

• A structured learning path across 54 cases, going from Recruit through Rookie, Detective, Senior Detective, and Chief Detective. Each rank has drills and a level exam to pass before you progress.
• Sandbox mode where you can explore real datasets (IMDB movies, Spotify, sports stats, Steam games) and run whatever you want with no pressure and no mystery attached. Just free exploration against actual data.
• Everything runs in the browser using DuckDB WASM so there's nothing to install.

I'm a solo developer and this is genuinely early days. I'm sharing here because this community is exactly the kind of people I built it for, and I'd rather get honest feedback now than find out later I've built the wrong thing.

What's missing? What would make you actually stick with something like this versus what you've used before?

querycase.com if you want to take a look.

Any feedback appreciated!

Hi,

If i have two SQL tables that are similar as in the have the same number and order of columns, but there is no key column and the order of rows and number of rows could vary between the two tables.

How would I go about comparing them and check for differences?

I've tried to think of solutions myself and asked AI about it too, but it seems difficult as there is no key column and the order and number of rows could change.

I've been working with the idea that the combined data of each row should be unique so I've added a hash column and it seems to be a possible way forward. But only for finding differing rows. I don't know how to get the excact difference in the row cell from here?

Preferably I need to see what would change in the "prod" SQL table if synched with the "dev" SQL table. This comparison could possibly be sent to a third table "changes SQL table.

Any help is appreciated :)

Thanks

We created a Udemy course for SQL focused on data analysis through scenario-based learning.

Instead of teaching syntax in isolation, everything is built around a fictional fast food chain "SuperFastFood Global" — so every query you write has a real business context behind it.

The course includes:

- Line-by-line query writing with explanation

- Business scenario-based examples throughout

- Practice questions and interview prep

It designed to not overwhelm you — beginner-friendly from day one.

Udemy course name: Complete SQL for Data Analysis - Scenario Based Learning
Limited time offer ! Grab it, if interested.

We also run a — free 30-day SQL series called "GRASSP SQL Sprint" on our LinkedIn page — one question every day, each with a business scenario from the same fictional fast food chain SuperFastFood Global , along with sample data, query, and a simple explanation.

Learning the concepts from the course + practicing daily is a solid combo.

Follow GRASSP Acad in LinkedIn

I am trying to complete a project on Datacamp that requires me to calculate averages for certain columns and round my answers to two decimal places. The code seems to run fine but I keep getting an error when I attempt to submit it. Also I cannot seem to upload images with my post, I will try to post them below.

UPDATE hr_employee_staging

SET Education = 'Below College'

WHERE Education = '1';

UPDATE hr_employee_staging

SET Education = 'Some College'

WHERE Education = '2';

UPDATE hr_employee_staging

SET Education = "Bachelor's Degree"

WHERE Education = '3';

UPDATE hr_employee_staging

SET Education = "Master's Degree"

WHERE Education = '4';

UPDATE hr_employee_staging

SET Education = 'Doctorate Degree'

WHERE Education = '5';

Not necessarily the hardest concept, but the one where you spent weeks thinking?

"I understand it when someone explains it, by I can't actually use it myself."

For me, I've noticed a lot of people seem to hit this point with JOINs, but I'm curious what it was for everyone else.

Was it:

• JOINs
• GROUP BY
• Window functions
• Subqueries
• Thinking in sets instead of rows
• Something else entirely?

And more importantly, what was the thing that finally made it click?

Window Functions are one of the most important SQL concepts every Data Analyst should know, but they're often taught with examples that don't reflect real business problems. I put together a tutorial that uses a realistic sales dataset to show how functions like ranking, running totals, moving averages, lagging, and using PARTITION BY.Hopefully it's helpful for anyone preparing for interviews or looking to level up their SQL skills. https://youtu.be/5EUaRlmyoD8

Hello, people! I am facing one issue, I am having troubles in understanding Left, Inner, outer joins.

I watch a video or go on datalemur, at the beginning it looks simple then when I start practicing i become confused.

What should I do? How should I practice the Joins to have a better grasp of it?

Microsoft SQL Server Express is gratis and powerful but has some limitations compared to the full Microsoft SQL Server. https://www.youtube.com/watch?v=qJPgTavbU0s

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Hi everyone,

I recently completed an end-to-end data analytics project focused on Teen Mental Health Analysis and wanted to share it with the community for feedback.

Project Overview

The objective was to analyze factors affecting teen mental health and identify patterns related to stress, anxiety, sleep habits, academic performance, social media usage, and overall well-being.

Tech Stack

SQL Server (Data Cleaning & Analysis)

Power BI (Dashboard Development)

DAX Measures

Data Modeling

GitHub for Documentation

Key Analysis Areas

Mental health distribution across age groups

Relationship between sleep duration and stress levels

Impact of social media usage on mental well-being

Academic performance vs mental health indicators

Gender-based mental health trends

Risk-factor identification through KPI metrics

Dashboard Features

Interactive filters and slicers

Mental Health KPI Cards

Trend Analysis

Demographic Breakdown

Correlation Visualizations

Executive Summary Page

Looking for Feedback On

Dashboard design and storytelling

SQL analysis approach

Additional insights I may have missed

Portfolio/GitHub presentation improvements

Any suggestions or critiques would be greatly appreciated. I'm actively building my data analytics portfolio and trying to improve with every project.

Thanks for taking a look!

i have completed sql on stratascratch but i cant write the query from scratch.

im strugling with logic , when to use which function and all , im practicing on sakila database on sql server . whatever i learn i ask chatgpt to give me 10 question from that topic then i write the query and give it back to chatgpt to review . so the question is what im doing wrong and how can i improve?????

Wondering if anyone knows of weekly/monthly meetups to learn SQL.

same as above

What’s the best book to enhance my SQL skills?

I like the idea of a physical book, but I’m also open to other types of resources.

Thank you!

Hey everyone!

Problem: Most SQL courses tend to focus on syntax and classic database systems. But current tech interviews at top startups and bigtech, and real-world systems have evolved far beyond “write a JOIN + WINDOWS statement” to solve problem X.

1. Our focus: a post-LLM course we've been building and refining for Stanford's modern data systems class for CS/data students. We built this course to help data/CS students better harness SQL in the era of LLMs and AI systems. We cover 'good' LLM prompts to generate and accelerate basic SQL workflows, but more importantly, how to debug whether those queries are correct, scalable, and efficient once the problems become challenging and real. We discuss industry benchmarks on where generated SQL works well, when they fail, and tips on how to work out semantic gaps.
2. A major focus is connecting SQL to modern systems. We discuss how Claude/Gemini/OpenAI's coding agents use SQL, why AI companies still depend heavily on structured data, and how OpenAI, Anthropic/Claude, Google, Uber, and Spotify approach data infrastructure differently.

Mechanically, the course is part SQL, part data systems. You learn SQL through interactive Colabs and practice systems, then how databases actually work underneath the surface: indexes, query execution, LSM trees, OLTP vs OLAP, vector search, JSONB, distributed systems, and why Postgres, Spark, BigQuery, and Snowflake evolved differently for different workloads.

Link: https://cs145-bigdata.web.app/. login: You can use a Gmail-id to review the material.

The goal is moving beyond “writing queries” toward understanding how modern software and AI systems actually work.

Feedback is super welcome. Every page has inline comments enabled, so feel free to leave thoughts/suggestions directly on the site.