🚨 New Video is LIVE — A Concept Most SQL Developers Get Wrong! 🚨

CTE, Temp Table, hSubquery…
Most people know them.
But very few know when to actually use what 👀

In this video, I’ve explained:

✅ Independent vs Correlated Subquery
✅ CTE vs Temp Table
✅ Which one executes first
✅ Which approach is best for interviews & real projects

If you’re preparing for:
• SQL interviews
• Data Analyst / Data Engineer roles
• Real-world SQL work

👉 This video will genuinely clear your confusion.

🎥 Watch now:
👉 Most SQL Developers Get This Wrong 🤯 | CTE vs Temp Table vs Subquery Explained
https://youtu.be/d5Amr7D-5tY

⚠️ Challenge for you:
After watching, tell me in comments —

Which one do you use the most: CTE / Temp Table / Subquery?

Let’s see who really understands SQL 🔥

#sql #dataengineer #datanalysis #sqlinterviewquestions

As promised previously I am back with this

Please watch it and let me know in comments if you liked it

Keep supporting ,keep learning ♥️

📘 Struggling with SQL? Maybe it’s not you… it’s how you’re learning.

Most people jump between random tutorials and get stuck.

But SQL becomes much easier when you follow a structured path:

👉 Basics → Queries → Joins → Indexes → Real-world concepts

This SQL handbook does exactly that — clean, simple, and beginner-friendly.

💡 Stop collecting resources.
Start following one clear roadmap.

Consistency > random learning.

If you’re serious about Data Engineering, start treating SQL like a skill — not just syntax 🚀

In my opinion the best answer here is option 2

Clustering does not always improver performance especially when you are dealing with some small dataset ,at that point ,manual clustering does not make sense

Hey Guys
My apologies

I have been really busy these days,not getting enough time to focus on our community.

Stay tuned , I will be back with something interesting

Here is a job opportunity for Airtel payments bank for Gurgoan

Role-Data Analytics
Level-A.M./Manager

Location-Gurgaon
Department- Finance BPA

Job Description-
1- Extract, analyze, and validate data from AWS databases using efficient and accurate SOL queries
2- Write optimized queries to join, aggregate, and transform large datasets into meaningful business insights through Python or SQL Languages,
3- Leverage Power BI to visualize data and deliver intuitive dashboards and reports for business stakeholders
4 Validate analytical outputs against source tables to ensure data accuracy and reliability
5- Support the BPA team with actionable insights to drive reven ue and cost planning discussions 6- Apply analytical techniques to identify trends, variances, and drivers impacting business performance
7- Amazon Qyciksight and Python knowledge would be an added advantage.

Range 12 lpa (negotiatable)

Immediately joiner (max 1 month)

Let me know if anyone is looking for a job change
Can get you referred for this job opportunity

Ping me on linkedin

Hey guys
Reposting it

The minimum experience for this position is 1-1.5 years

This is a good opportunity offering good salary

Let me know if you are interested

Most people learn SQL like this:

SELECT → JOIN → GROUP BY

…but ignore one of the most useful concepts in reporting:

💡 PIVOT

Sooner or later, every Data Analyst / Data Engineer faces this requirement:

🧾 “Convert rows into columns.”

That’s exactly where PIVOT helps 🚀

It’s not just an interview topic —
it’s heavily used in dashboards, reporting, and business analytics.

💡 Real SQL growth starts when you think beyond syntax and focus on:
👉 “How will users consume this data?”

Have you used PIVOT in real projects yet? 👀

🚨 Upcoming SQL Interview Challenge 🚨

Most SQL developers know string functions…
But very few can solve THIS interview question correctly 👀

🎯 Problem:
Split a full customer name into:
✅ First Name
✅ Middle Name
✅ Last Name

Sounds easy? 😏

Now handle:
⚠️ NULL values
⚠️ Single names
⚠️ Multiple name combinations


New YouTube video dropping soon 🔥

Let’s see how many of you can solve it before the solution goes live 👇

🚨 New SQL Interview Video is LIVE 🚨

Can you split a full name into:
✅ First Name
✅ Middle Name
✅ Last Name

Sounds simple… until edge cases enter the game 😏

In this video, I solve a very interesting SQL interview question involving:
✔ String functions
✔ NULL handling
✔ Real-world logic

🎥 Watch now:
👉 Tricky SQL Interview Question in Hindi | Split Full Name into First, Middle & Last Name in SQL
https://youtu.be/_kcVqMJU72A

Let me know honestly…
Could YOU solve it before watching? 👀

🚨 Quick SQL Reality Check

Most developers think:

COUNT(*) = COUNT(Column)

But that’s not always true 👀

A single NULL value can completely change the result.

I recorded a quick 30-second Short explaining the difference with a simple example.

🎥 Watch here:
👉 [Paste YouTube Shorts Link]

Trust me, this is one concept worth remembering for SQL interviews and real-world projects.

Or, if you want something more aggressive:

⚠️ SQL Interview Trap

What will these return?

COUNT(*)

COUNT(Salary)

Same answer? 🤔

Most people get this wrong because of NULL values.

I explained it in a quick YouTube Short👇

🎥 Watch Now:
👉
https://youtube.com/shorts/1rHHZmMHx6E?feature=share

Did you know the answer before watching? 😏

Python File Handling

File handling is one of the most important skills in Python, especially for Data Engineering and Automation.

📂 Reading Files – Load data from text files, logs, and reports.

✍️ Writing Files – Create, update, and save data to files.

📊 CSV Processing – Read, transform, and analyze structured data stored in CSV files.

🔄 JSON Handling – Work with API responses and exchange data between applications.

💡 Most real-world applications and data pipelines rely heavily on CSV and JSON files. Learning file handling helps you automate tasks and work with data efficiently.