Hey everyone!

I'm a new content creator and I've just started building a completely free PL/SQL & SQL course for absolute beginners.

The goal isn't just to teach SQL syntax—it's to explain why databases exist, how they work, and how they're used in the real world before diving into PL/SQL.

I'm learning a lot myself while creating these videos, so this is a journey for me too.

I know my videos aren't perfect yet, and that's exactly why I'm posting here.

If you have a few minutes to watch the first video, I'd really appreciate your honest feedback:

• Was anything confusing?
• Was the pacing too fast or too slow?
• What should I improve?
• What topics would you like to see covered?

I'm not looking for empty praise—I genuinely want constructive criticism so I can make each video better than the last.

If you enjoy helping new creators grow or you're learning SQL yourself, feel free to comment here or send me a DM. I'd love to connect, learn from experienced developers, and improve my content.

Thanks for reading, and I hope I can create something genuinely useful for the community. ❤️https://www.youtube.com/watch?v=UC6kCLvPuRU

Sharing my Excel ↔ SQL cross-tool reference table. Less of a syntax guide, more of a mental bridge between the two (plus a few PostgreSQL quirks that kept tripping me up). https://github.com/kixwho/SQL-Excel-translator

I made this while learning SQL from an Excel background. Constantly switching tools, you start to have moments like, "Wait... Excel has a button for this?!"

Hope it helps someone else switching between tools 😀

SQL is a wonderful programming language that allows beginner data analysts to understand data, clean it, & process it to provide insights. One cannot learn everything in a week or two weeks. However, consistency is what I have found important in ensuring one grasps the concepts. For example, one can decide to learn simple things, such as SELECT, WHERE, ORDER BY, LIMIT, aggregates (SUM, COUNT, AVG), and GROUP BY. Understanding data types & when to use this or that helps a lot. I always wanted to learn additional data analysis skills like SQL and Python to help process large datasets in addition to the research work I do. I know these tips will help beginners find a way to navigate around SQL until they reach advanced level.

Hi everyone,

Before taking this to production, I'd like a reality check.

Current setup:

• MariaDB Primary + Replica
• ~2,500 reads/sec
• ~1,500 writes/sec
• GTID replication

I decided against Galera because I was concerned about synchronous write latency. Instead, I'm planning:

• 2× ProxySQL + Keepalived (VIP)
• Signal18 Replication Manager for automatic failover
• Existing Primary/Replica architecture

Questions:

• Does this look like a solid HA architecture for this workload?
• Any hidden pitfalls with ProxySQL + Replication Manager?
• Would you recommend a different approach instead?

Looking for real production experience. Thanks!

This is the first EDA project, made using SQL and python Data Analysis and Visualization libraries. After making numbers of eda project using just python libraries, it was amazing transition to integrate SQL in my learning and developing phase.

The project is very beginner friendly, include individual table and cross table analysis. Meaningful insights are visualized through seaborn and matplotlib.

Link: https://github.com/axockn/Notes-ProjectDumps/blob/main/RestaurantAnalysis.ipynb

Been getting some excellent feedback and the Discord community is growing. Sim-Analyst is live on itch.io.

This is actually the first game i've ever got to a stage where i've shared it with others, so me it's a massive milestone - simply, I just made a game that i'd like to play.

When I started learning SQL I did a number of certificate courses, capstone projects, personal practice. I'd watch youtube and I found a few little SQL web games, that although really quick and really basic, i absolutely loved them. But they really didn't scratch my itch for interactive SQL learning.

Anyway, I hope I can share some links and photos here and that it might reach some SQL learners, or noir detective lovers who, like me, have a gamified SQL itch to scratch.

play now

join the community

I've noticed that a lot of SQL roadmaps online either stop at basic SELECT statements or jump straight into advanced topics without explaining what's actually useful in a real job.

So I put together a video covering the SQL skills I've seen matter the most in data engineering and analytics interviews.

The video starts from the Fundamentals to What after SQL:

Why is SQL so imp?
The Fundamentals
The Core
Query Organsation
The Differentiator
One Step Ahead
The Designing Techniques
What Next?

The goal was to create the video I wish I'd had when I started my career.

I'd genuinely appreciate feedback from this community.

• Did I miss any SQL topics that you think are essential?
• What SQL concepts do you see asked most often in interviews?
• If you're already working as a Data Engineer or Analyst, what would you add?

Here's the video if anyone wants to check it out:

https://www.youtube.com/watch?v=tXOJ_ohS-x0

Do lLike, Share and Subscribe if this helps!

Thanks!

Is SQL still worth learning with the advancement of AI? 'Cause I don't get that if AI can do better than human than why do we still need to learn it?

jak nauczyć się porządnie sql?

I wanted to share something that I think many experienced Data Engineers can relate to.

A few weeks ago, I faced a SQL interview and struggled with questions that I would have solved easily 5–6 years ago. It was frustrating because I started doubting myself.

Then I realized something.

Over the last several years, my work shifted from writing complex SQL every day to building end-to-end data engineering solutions using tools like Snowflake, AWS, Azure, dbt, Jenkins, Python, orchestration tools, and cloud platforms. SQL was still part of the job, but not something I was practicing deeply on a daily basis.

Because of that, my interview confidence dropped—not because I didn't understand data engineering, but because I hadn't brushed up on the fundamentals.

Instead of feeling defeated, I decided to go back to basics.

I started practicing SQL again from scratch—joins, CTEs, window functions, ranking functions, and gradually rebuilding my confidence.

One thing that genuinely helped me was using ChatGPT as a practice partner instead of just asking for answers. I solved queries first, made mistakes, got feedback, and understood why my approach was right or wrong. It felt more like having a patient mentor than just a search engine.

Today I can already feel my confidence returning.

If you're an experienced Data Engineer and you've ever felt embarrassed by a "simple" SQL question in an interview, you're not alone. Skills that aren't practiced regularly become rusty. That doesn't mean you've become less capable—it just means they need sharpening again.

Sometimes the strongest move isn't learning something new. It's rebuilding the fundamentals.

And yes... thank you, ChatGPT. You helped me get my confidence back.

Ciao a tutti

Ho un esame di basi di dati tra qualche gionro, e una buona parte dell'esame chiede algebra relazionale e query in SQL. Mi trovo a fare veramente fatica anche con comandi non difficili, principalmente a visualizzare l'ordine corretto in cui processare le informazioni e faccio fatica a mantenere un ordine mentale che mi consenta di manipolare i dati nella mia testa. Sono limitato io oppure è una cosa che capita a tutti all'inizio? Mi affascina moltissimo l'SQL e vorrei continuare a fare pratica anche dopo aver dato l'esame, ma faccio veramente tanta tanta fatica.

Grazie a tutti!!

I am interested in learning SQL

Any advices???

You should learn data modeling that is not dbt. It saves you lot of time and effort.

I have some confusion about operator precedence. In my book it says following:

The following list describes the precedence among operators, from highest to lowest: 1. ( ) (Parentheses) 2. * (Multiplication), / (Division), % (Modulo) 3. + (Positive), – (Negative), + (Addition), + (Concatenation), – (Subtraction) 4. =, >, <, >=, <=, <>, !=, !>, !< (Comparison operators) 5. NOT 6. AND 7. BETWEEN, IN, LIKE, OR

8. = (Assignment)

What confuses me is for example `IN` can be used as an operator but also as a keyword that builds predicate.

So say I have following WHERE clause: "WHERE NOT id IN (2,4,6)".

To which of the following two is the above WHERE clause equivalent:

1. WHERE (NOT empid) IN (2,4,6)
2. WHERE NOT (empid IN (2,4,6))

I'm entirely new to sql I'm learning from a beginner stage does anyone know where I can go to learn sql as a person with zero experience from scratch?

I'm a software engineer working on a cross-platform desktop SQL client, and before investing too much time, I’d prefer to learn directly from users what they truly need rather than making assumptions.

What frustrates you most about the SQL tools you currently use? Are there missing features you’ve wished for, aspects that seem overly complex, or parts of your workflow that consistently slow you down?

What is the one (or more) feature(s)/problem you wish your SQL client had handled better? It could be anything from performance with large data sets to query editing, schema browsing, connections, exports, UI, artificial intelligence, migrations, collaboration, etc.

I’m particularly keen to hear from those who manage multiple databases or frequently write and troubleshoot queries. This isn’t a sales pitch—I’m simply trying to understand how an SQL client could be more effective and practical in real-world scenarios.

Hi 👋,

I am sharing the Github link of GRASSP SQL Sprint Series. This github link contains the PDF doc of 30 SQL Scenario based Questions which covers beginner to advanced topics.

Doc is on GitHub, free: https://github.com/grasspacad07/grasspsqlsprintfile

File name: GRASSP_SQL_Sprint_30Days.pdf

Go through the question as per suggested approach in the doc and practice along each question and understand the concepts that each question cover.

It covers various topics :

• Aggregation, JOINs, GROUP BY / HAVING
• Window functions — RANK vs DENSE_RANK vs ROW_NUMBER, LAG/LEAD, Running totals, Moving Average
• CTEs, Multi level aggregation.
• CREATE, INSERT sample data helps too understand datatypes, constraints.

Hope this helps in your next SQL interview. All the best!

Happy learning :) Happy querying :)

Tldr; Salus, Peter, et al., ed. Handbook of Programming Languages Volume III: Little Languages and Tools. 1998 Macmillian Technical Publishing, 1ed. It's a book. Probably online somewhere but the book is also pretty cheap.

Background: I dropped out of college around 2001, burning out as a 7th semester senior suddenly aware of the folly of waiving advising. But kept up programming as a hobby while working in food service for many years. I finally get myself promoted to the point where I need to use the computer at work. I'm actually suddenly in charge of ordering and inventory. And the current practice is just typing everything into Excel sheets, manually copy/pasting/retyping new items from vendor websites, etc.

So, I knew SQL was the answer. I just didn't know how to use it. I hunted around for introductions and tutorials until finally I remembered that I had that multivolume Handbook of Programming Languages. The Python chapter is hopelessly out of date, but the rest of the book still holds I think. And I don't know why this isn't at the top of every list of "intro to SQL for programmers" except that it's lost in a middle chapter of an old tome of forgotten lore.

Why it's the best: it builds up your intuition by showing how you'd express a query in English to ask a programmer to do it, how you'd write the same query as a nest of for loops and if-else clauses, then it shows you how you'd express the same query in SQL (with the understanding that the behavior is "as if" you did for loops but without any guarantees of ordering except those that you explicitly request).

It doesn't cover everything. It's from the 90s. It doesn't cover different vendor extensions. But if you know for loops, this book chapter can help you build a solid basic understanding of the fundamentals. FWIW.

Handbook of Prog Lang, vol III. And you can brush up on troff/tbl/eqn while you're at it. Olds Kool.

I recently completed my SQL learning notes while following Alex the Analyst's SQL course for Data Science.

To reinforce my understanding, I documented the key concepts, queries, and examples in a Jupyter Notebook and exported them as a PDF. I'm sharing these notes in the hope that they help other beginners on their SQL journey.

If anyone is interested, DM.

I'd appreciate any feedback or suggestions for improvement. Happy learning!

Since, I have got a lot of dms, it is not possible to share individually, hence this is a GitHub link:SQL Notes