SQL Junction pinned ยซ๐จ New Video is LIVE โ A Concept Most SQL Developers Get Wrong! ๐จ CTE, Temp Table, hSubqueryโฆ Most people know them. But very few know when to actually use what ๐ In this video, Iโve explained: โ
Independent vs Correlated Subquery โ
CTE vs Temp Table โ
Whichโฆยป
SQL Junction
I have created this video and will post it in next week
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 โฅ๏ธ
Please watch it and let me know in comments if you liked it
Keep supporting ,keep learning โฅ๏ธ
โค3
๐ Struggling with SQL? Maybe itโs not youโฆ itโs how youโre learning.
Most people jump between random tutorials and get stuck.
But SQL becomes much easier when you follow a structured path:
๐ Basics โ Queries โ Joins โ Indexes โ Real-world concepts
This SQL handbook does exactly that โ clean, simple, and beginner-friendly.
๐ก Stop collecting resources.
Start following one clear roadmap.
Consistency > random learning.
If youโre serious about Data Engineering, start treating SQL like a skill โ not just syntax ๐
Most people jump between random tutorials and get stuck.
But SQL becomes much easier when you follow a structured path:
๐ Basics โ Queries โ Joins โ Indexes โ Real-world concepts
This SQL handbook does exactly that โ clean, simple, and beginner-friendly.
๐ก Stop collecting resources.
Start following one clear roadmap.
Consistency > random learning.
If youโre serious about Data Engineering, start treating SQL like a skill โ not just syntax ๐
โค1๐1
Which of these is not always TRUE in Snowflake for query optimization?
Final Results
30%
Increasing Warehouse Size
45%
Clustering always improves performance
38%
Clustering Keys
15%
Result Cache
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
Clustering does not always improver performance especially when you are dealing with some small dataset ,at that point ,manual clustering does not make sense
๐2
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
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.
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.
Let me know if anyone is looking for a job change
Can get you referred for this job opportunity
Ping me on linkedin
Can get you referred for this job opportunity
Ping me on linkedin
SQL Junction
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 queriesโฆ
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
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
๐4โค1
Most people learn SQL like this:
SELECT โ JOIN โ GROUP BY
โฆbut ignore one of the most useful concepts in reporting:
๐ก PIVOT
Sooner or later, every Data Analyst / Data Engineer faces this requirement:
๐งพ โConvert rows into columns.โ
Thatโs exactly where PIVOT helps ๐
Itโs not just an interview topic โ
itโs heavily used in dashboards, reporting, and business analytics.
๐ก Real SQL growth starts when you think beyond syntax and focus on:
๐ โHow will users consume this data?โ
Have you used PIVOT in real projects yet? ๐
SELECT โ JOIN โ GROUP BY
โฆbut ignore one of the most useful concepts in reporting:
๐ก PIVOT
Sooner or later, every Data Analyst / Data Engineer faces this requirement:
๐งพ โConvert rows into columns.โ
Thatโs exactly where PIVOT helps ๐
Itโs not just an interview topic โ
itโs heavily used in dashboards, reporting, and business analytics.
๐ก Real SQL growth starts when you think beyond syntax and focus on:
๐ โHow will users consume this data?โ
Have you used PIVOT in real projects yet? ๐
โค3
๐จ Upcoming SQL Interview Challenge ๐จ
Most SQL developers know string functionsโฆ
But very few can solve THIS interview question correctly ๐
๐ฏ Problem:
Split a full customer name into:
โ First Name
โ Middle Name
โ Last Name
Sounds easy? ๐
Now handle:
โ ๏ธ NULL values
โ ๏ธ Single names
โ ๏ธ Multiple name combinations
New YouTube video dropping soon ๐ฅ
Letโs see how many of you can solve it before the solution goes live ๐
Most SQL developers know string functionsโฆ
But very few can solve THIS interview question correctly ๐
๐ฏ Problem:
Split a full customer name into:
โ First Name
โ Middle Name
โ Last Name
Sounds easy? ๐
Now handle:
โ ๏ธ NULL values
โ ๏ธ Single names
โ ๏ธ Multiple name combinations
New YouTube video dropping soon ๐ฅ
Letโs see how many of you can solve it before the solution goes live ๐
โค3
๐จ New SQL Interview Video is LIVE ๐จ
Can you split a full name into:
โ First Name
โ Middle Name
โ Last Name
Sounds simpleโฆ until edge cases enter the game ๐
In this video, I solve a very interesting SQL interview question involving:
โ String functions
โ NULL handling
โ Real-world logic
๐ฅ Watch now:
๐ Tricky SQL Interview Question in Hindi | Split Full Name into First, Middle & Last Name in SQL
https://youtu.be/_kcVqMJU72A
Let me know honestlyโฆ
Could YOU solve it before watching? ๐
Can you split a full name into:
โ First Name
โ Middle Name
โ Last Name
Sounds simpleโฆ until edge cases enter the game ๐
In this video, I solve a very interesting SQL interview question involving:
โ String functions
โ NULL handling
โ Real-world logic
๐ฅ Watch now:
๐ Tricky SQL Interview Question in Hindi | Split Full Name into First, Middle & Last Name in SQL
https://youtu.be/_kcVqMJU72A
Let me know honestlyโฆ
Could YOU solve it before watching? ๐
๐2โค1
SQL Junction pinned ยซ๐จ New SQL Interview Video is LIVE ๐จ Can you split a full name into: โ
First Name โ
Middle Name โ
Last Name Sounds simpleโฆ until edge cases enter the game ๐ In this video, I solve a very interesting SQL interview question involving: โ String functions โโฆยป
๐จ Quick SQL Reality Check
Most developers think:
COUNT(*) = COUNT(Column)
But thatโs not always true ๐
A single NULL value can completely change the result.
I recorded a quick 30-second Short explaining the difference with a simple example.
๐ฅ Watch here:
๐ [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:
โ ๏ธ SQL Interview Trap
What will these return?
COUNT(*)
COUNT(Salary)
Same answer? ๐ค
Most people get this wrong because of NULL values.
I explained it in a quick YouTube Short๐
๐ฅ Watch Now:
๐
https://youtube.com/shorts/1rHHZmMHx6E?feature=share
Did you know the answer before watching? ๐
Most developers think:
COUNT(*) = COUNT(Column)
But thatโs not always true ๐
A single NULL value can completely change the result.
I recorded a quick 30-second Short explaining the difference with a simple example.
๐ฅ Watch here:
๐ [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:
โ ๏ธ SQL Interview Trap
What will these return?
COUNT(*)
COUNT(Salary)
Same answer? ๐ค
Most people get this wrong because of NULL values.
I explained it in a quick YouTube Short๐
๐ฅ Watch Now:
๐
https://youtube.com/shorts/1rHHZmMHx6E?feature=share
Did you know the answer before watching? ๐
โค1
Python File Handling
File handling is one of the most important skills in Python, especially for Data Engineering and Automation.
๐ Reading Files โ Load data from text files, logs, and reports.
โ๏ธ Writing Files โ Create, update, and save data to files.
๐ CSV Processing โ Read, transform, and analyze structured data stored in CSV files.
๐ JSON Handling โ Work with API responses and exchange data between applications.
๐ก 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.
File handling is one of the most important skills in Python, especially for Data Engineering and Automation.
๐ Reading Files โ Load data from text files, logs, and reports.
โ๏ธ Writing Files โ Create, update, and save data to files.
๐ CSV Processing โ Read, transform, and analyze structured data stored in CSV files.
๐ JSON Handling โ Work with API responses and exchange data between applications.
๐ก 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.
๐2
Expand your job search to increase your chances of becoming a data analyst.
Some alternative roles to explore:
1. ๐๐๐๐ถ๐ป๐ฒ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Focuses on using data to improve business processes and decision-making.
2. ๐ข๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐ ๐๐ป๐ฎ๐น๐๐๐: Specializes in analyzing operational data to optimize efficiency and performance.
3. ๐ ๐ฎ๐ฟ๐ธ๐ฒ๐๐ถ๐ป๐ด ๐๐ป๐ฎ๐น๐๐๐: Uses data to drive marketing strategies and measure campaign effectiveness.
4. ๐๐ถ๐ป๐ฎ๐ป๐ฐ๐ถ๐ฎ๐น ๐๐ป๐ฎ๐น๐๐๐: Analyzes financial data to support investment decisions and financial planning.
5. ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐๐ป๐ฎ๐น๐๐๐: Evaluates product performance and user data to help product development.
6. ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ป๐ฎ๐น๐๐๐: Conducts data-driven research to support strategic decisions and policy development.
7. ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Transforms data into actionable business insights through reporting and visualization.
8. ๐ค๐๐ฎ๐ป๐๐ถ๐๐ฎ๐๐ถ๐๐ฒ ๐๐ป๐ฎ๐น๐๐๐: Utilizes statistical and mathematical models to analyze large datasets, often in finance.
9. ๐๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐๐ป๐๐ถ๐ด๐ต๐๐ ๐๐ป๐ฎ๐น๐๐๐: Analyzes customer data to improve customer experience and drive retention.
10. ๐๐ฎ๐๐ฎ ๐๐ผ๐ป๐๐๐น๐๐ฎ๐ป๐: Provides expert advice on data strategies, data management, and analytics to organizations.
11. ๐ฆ๐๐ฝ๐ฝ๐น๐ ๐๐ต๐ฎ๐ถ๐ป ๐๐ป๐ฎ๐น๐๐๐: Analyzes supply chain data to optimize logistics, reduce costs, and improve efficiency.
12. ๐๐ฅ ๐๐ป๐ฎ๐น๐๐๐: Uses data to improve human resources processes, from recruitment to employee retention and performance management.
Some alternative roles to explore:
1. ๐๐๐๐ถ๐ป๐ฒ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Focuses on using data to improve business processes and decision-making.
2. ๐ข๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐ ๐๐ป๐ฎ๐น๐๐๐: Specializes in analyzing operational data to optimize efficiency and performance.
3. ๐ ๐ฎ๐ฟ๐ธ๐ฒ๐๐ถ๐ป๐ด ๐๐ป๐ฎ๐น๐๐๐: Uses data to drive marketing strategies and measure campaign effectiveness.
4. ๐๐ถ๐ป๐ฎ๐ป๐ฐ๐ถ๐ฎ๐น ๐๐ป๐ฎ๐น๐๐๐: Analyzes financial data to support investment decisions and financial planning.
5. ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐๐ป๐ฎ๐น๐๐๐: Evaluates product performance and user data to help product development.
6. ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ป๐ฎ๐น๐๐๐: Conducts data-driven research to support strategic decisions and policy development.
7. ๐๐ ๐๐ป๐ฎ๐น๐๐๐: Transforms data into actionable business insights through reporting and visualization.
8. ๐ค๐๐ฎ๐ป๐๐ถ๐๐ฎ๐๐ถ๐๐ฒ ๐๐ป๐ฎ๐น๐๐๐: Utilizes statistical and mathematical models to analyze large datasets, often in finance.
9. ๐๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐๐ป๐๐ถ๐ด๐ต๐๐ ๐๐ป๐ฎ๐น๐๐๐: Analyzes customer data to improve customer experience and drive retention.
10. ๐๐ฎ๐๐ฎ ๐๐ผ๐ป๐๐๐น๐๐ฎ๐ป๐: Provides expert advice on data strategies, data management, and analytics to organizations.
11. ๐ฆ๐๐ฝ๐ฝ๐น๐ ๐๐ต๐ฎ๐ถ๐ป ๐๐ป๐ฎ๐น๐๐๐: Analyzes supply chain data to optimize logistics, reduce costs, and improve efficiency.
12. ๐๐ฅ ๐๐ป๐ฎ๐น๐๐๐: Uses data to improve human resources processes, from recruitment to employee retention and performance management.
๐1