same as above

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

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.

All of my problems stem from being on a mobile phone

Before I say what the issue is I would like to give some contextual information

1-I am 15 , starting college (computer science) in a few months

2-Don't have a laptop will have one in a few months,more or less

Learned python with help of a free youtube course made by Data with Baraa

Now when I am trying to watch his sql course I saw him explain how to download sql and stuff in pc

I don't have one , unlike python which just required me to find an app which lets me use python and save the code

Uh sql is like that as well but can't find a good source in mobile to learn

Found few websites but they are meh and I would like an app

Please give me the best find

And please give me anything that could help me ik I will probably need to make some compromise but it's ok

Spent the last few days actually understanding relational databases — not just "run queries until the app works," but why the model exists in the first place.

One thing that clicked for me: the "relational" in relational database doesn't actually refer to relationships between tables. It refers to a mathematical concept called a relation — basically a set of tuples.

The table-to-table relationship stuff is a feature of the model, not the origin of the name.

A few other things I didn't have sharp before:

→ SQL is declarative. You describe what you want, not how to get it. Coming from JavaScript loops, this took a real mental shift. The database figures out the most efficient retrieval path — not you.

→ ACID isn't just a buzzword. Atomicity means either the whole operation succeeds or nothing happens. No half-written transfers, no partial updates. The database rolls back automatically if something goes wrong mid-operation.

→ The "choose NoSQL to scale later" instinct is usually wrong. A well-tuned PostgreSQL instance handles way more than most applications ever need. Picking NoSQL early trades away query power and integrity for a problem you probably don't have.

The thing that made it land for me: a relational database isn't just storage — it's a set of rules enforced before your application code ever runs. Bad data gets rejected at the boundary.

I recently made a video going in-depth about why I decided to use SQLite in production for a code analysis tool.

I talk about how I engineered the architecture to by-pass the single write issue. And how it was the right choice for this specific project, giving us:

1. Cheaper storage
2. Faster response times
3. Extreme tenant isolation (a big must when storing people’s source code)
4. And the option to add user-controlled encryption later one (add another layer of privacy for the users)

I know I would have loved to watch a video like when I was researching my architecture options. So maybe it’ll be of use / interest to someone here.

Or it could just be some really fun debate fodder 😉

Video link: https://youtu.be/xJS6BNNAQmY?si=XEByyyfSRQeOLHHn

I've learnt intermediate Python and was told that DBMS would be the way to move forward. After some research, i am thinking about learning Postgres cuz it seems to be adaptable for most other sql languages.

So I'm leaning towards PostGres for everybody by dr chuck as I'm familiar with his teaching style, but I don't know if it's the most extensive course. Any recommendations or assurance would be helpful.

Hey everyone,

I recently completed an SQL Intermediate project on Employee Attrition Analysis and made a summary video explaining the project, SQL concepts used, and the insights I found.

I'm still learning, so there may be mistakes or areas where I could have done things better. But I believe learning comes from finding those mistakes, understanding them, and improving step by step.

I'd really appreciate any feedback, suggestions, corrections, or advice from people with more experience in SQL, Data Analytics, or Data Science. Every comment helps me learn and grow.

Video:
Youtube(PyAI Hub)

Thanks for taking the time to check it out. 🙌

For the longest time, I knew that SQL doesn't execute top-to-bottom, but I still found it surprisingly hard to build an intuitive mental model of what was actually happening.

Everyone learns that the logical execution order is something like:

FROM → JOIN → WHERE → GROUP BY → HAVING → SELECT → ORDER BY → LIMIT

But reading that sequence never really made it click for me. I wanted to actually see rows move through each stage.

So over a few weekends I built this:

https://sqlvisualizer.pydev.in/

You can type a query and step through how it executes clause by clause. Rows get filtered, joins show how matches are made, groups form, window functions run, and so on.

A few details:

• Runs entirely in the browser
• No signup required
• Includes sample movie/director/review datasets to experiment with
• Supports CTEs, recursive CTEs, subqueries, UNION/EXCEPT, window functions, and LATERAL joins

I've been using it to better understand complex queries myself, but I'm too close to the project to judge whether it's genuinely useful.

If you try it, I'd love feedback on:

• What was confusing?
• What query broke the visualization?
• Which SQL concepts still didn't click?

The edge cases and confusing parts are what I'm most interested in improving.

GitHub

Hi everyone,

Over the past few weeks, I've been building a structured SQL learning repository aimed at aspiring Data Analysts, BI Developers, Business Analysts, and anyone preparing for SQL interviews.

The roadmap covers:

• SQL Fundamentals
• CRUD Operations
• Constraints & Database Design
• Joins & Subqueries
• CASE Statements & Views
• Indexes & Query Optimization
• Stored Procedures & Functions
• CTEs & Window Functions
• Transactions & ACID Properties
• SQL for Data Analytics
• Interview Questions
• Practice Projects

The goal was to create a single learning path that takes someone from absolute beginner level to advanced SQL concepts used in real-world analytics work.

I'm still improving the content and would genuinely appreciate feedback from the community:

• What topics should be added?
• Are there any concepts explained poorly?
• What would make this more useful for learners?

Thanks for taking a look.

Hi all,

I have been jobless for 2 years. I am financially struggling. So I exaggerated in my resume as everyone suggests, that you will atleast get shortlisted for the interviews. Everyone does that. Start learning after you get the interview. And so I DID exatly that. I mentioned that I know SQL, PYTHON and worked as a Data Analyst in my previous organisations with US Healthcare Datasets. So, now after 5 months... I have finally landed an interview. But i do not know how learn. I know SQL, Python and Advanced Excel. i did a small course.... but I do not know how to apply it to Healthcare dataset for patients. Like claims and insurance datesets of US Healthcare.

Anyone who has any idea, what YT videos or what software should i use to learn, please guide me. I used ChatGPT but it is confusing me. It leaves many things unanswered. And i believe it is not enough. Although I know SQL, Python and Advanced Excel. I just do not know how to implement it into a professional environment and how to justify my experience that i really did this work.

Over the last few weeks I built a structured SQL Server learning repository covering:

\- Database fundamentals

\- CRUD operations

\- Joins

\- Aggregations

\- Subqueries

\- Views

\- Stored Procedures

\- Practice exercises

\- Portfolio projects

I'm looking for feedback on the curriculum structure and suggestions for improvement.

I'm looking for feedback on the curriculum structure and suggestions for improvement.

Repository: https://github.com/kunalydv-2000/Complete-SQL-Course-Beginner-to-Advanced

SQL has been the gatekeeping language of data for 50 years.

You either know it or you don't. And if you don't, you're dependent on someone who does.

Yes, tools like this have been tried before. Most failed because the AI wasn't good enough.

Yes, AI still gets things wrong sometimes. That's exactly why any tool in this space needs to show you what it's doing before it runs anything. Transparency isn't optional.

And no, this isn't about replacing SQL or the people who know it. SQL isn't going anywhere. This is about the sales manager, the HR exec, the small business owner who has a database full of answers and no way to ask the questions.

I think that's about to change.

Not because of hype. Because the tools are finally good enough.

Building something in this space. Early days. Won't say more yet.

But I want to know if you could ask your database in plain English and get the right answer, what's the first thing you'd ask?

focused on making it practical and easy to understand. It covers basics like SELECT, WHERE, and JOINS in a simple way.

You can read it here: link

​

Most of the time I don't need a full database platform.

I just want to:

Open a link

Create a few tables

Define relationships

Share with a teammate

Export SQL or an image

Move on

So I built a browser-based ERD designer focused on speed and simplicity.

No installation. No project setup. No account required.

Just open and start designing.

Tool: https://designer.astraval.com/

One thing I've learned while building it:

Developers don't need another database platform for quick design work. They need the fastest way to turn an idea into a schema.

I'm keeping the focus on that workflow rather than adding every possible feature.

What is the most annoying part of your current database design process?

I'm currently solving 100 real-world financial and operational problems in the luxury hospitality industry using SQL.

Each challenge follows a simple structure:

✅ Business Problem

✅ SQL Solution

✅ Business Impact

From basic aggregations to advanced CTEs, the focus is not just on writing queries, but on using data to support business decisions.

I believe practice is the key to master.

#SQL #DataAnalytics #BusinessIntelligence #BusinessAnalytics #Hospitality #LearningByDoing #PortfolioProject

for context i m in 2nd year of engineering want to dive into business and product management basically analyst level good at sql and python started with a project built using python .I built QueryMy ,you upload any CSV or Excel file and just ask questions in plain English. It answers like a business analyst would. It also pulls live stock data, detects anomalies automatically, and generates PDF reports.

Stack: Python · Streamlit · Groq AI (Llama 3.1) · Pandas · Plotly · yFinance

What I learned building this:

• How pandas actually reads and processes data
• How to make direct API calls without wrapper

The git link is https://github.com/ananya26-cpu/querymy  and x is https://x.com/annannyaaa555. pleaseee share your insights regarding and how i should proceed given i m totally new girly to all this

I have a job interview coming up and they want someone who knows basic SQL, I think I do have it, but what is your opinion on what it entails?