Ankit Bansal

❌ Job security is not about working in a company with no history of layoffs.

❌ Job security is not about working in a company for a period of 10 or 20 years and expect loyalty from the employer.

❌ Job security is not about having a great relationship with your manager.



✅ Job security is having the confidence that you will get another job in no time after losing your current job.

✅ Job security is about upskilling yourself and having the confidence in the work that you have done.

✅ Job security is about having the emergency fund and knowing that being laidoff won't affect your financial situation.

Job security is all about your confidence, skills and a bit of financial planning.

#job #security #work #finacialplanning

❌ Job security is not about working in a company with no history of layoffs.

❌ Job security is not about working in a company for a period of 10 or 20 years and expect loyalty from the employer.

❌ Job security is not about having a great relationship with your manager.



✅ Job security is having the confidence that you will get another job in no time after losing your current job.

✅ Job security is about upskilling yourself and having the confidence in the work that you have done.

✅ Job security is about having the emergency fund and knowing that being laid off won't affect your financial situation.

Job security is all about your confidence, skills and a bit of financial planning.

#job #security #work #finacialplanning

Best practices for writing SQL queries:

1- Write SQL keywords in capital letters.

2- Use table aliases with columns when you are joining multiple tables.

3- Never use select *, always mention the list of columns in the select clause when deploying the code in production.

4- Add useful comments wherever you write complex logic. Avoid too many comments.

5- Use joins instead of subqueries when possible for better performance.

6- Create CTEs instead of multiple sub queries , it will make your query easy to read.

7- Join tables using JOIN keywords instead of writing join condition in where clause for better readability.

8- Never sort the data in sub queries , It will unnecessary increase runtime.

9- If you know there are no duplicates in 2 tables, use UNION ALL instead of UNION for better performance.

Anything else you want to add?

I talk about SQL, Tableau and data analytics on my youtube channel. Checkout the link in comment section.

#dataanalytics #sql #bestpractices

I am starting a series of end to end data engineering projects on my YouTube channel 📽️📽️


The idea is to learn data engineering concepts by doing hands on. You can follow along with me to start your data engineering and cloud journey.

I will try to keep things simple so that you guys can understand and follow along.


The first project is on AWS where we will be using s3 , glue , iam , Athena and quick sight services to do end to end projects. This project doesn't require much of the coding and all you need is an AWS account to get started.

I will be doing more complex projects in the future. Need all of your support and love 🙏

Link to the first project in the comments section.

#dataanalytics #dataengineering

For data analyst roles, SQL is the most in-demand skill, listed in a whopping 61% of job posts.

For data analyst roles on Indeed, SQL appears as follows:

1.7 times more than Python
2.5 times more than R
5.8 times more than machine learning
22.5 times more than Spark

If you want to become a data analyst, learning SQL should be at the top of your to-do list.


My next batch for SQL zero to hero course (Live classes) starting on Feb 14th.

Check out the comments section for the registration link.

#namaste #sql #datanalyst

I think data Wrangling is so natural to SQL that no other tool can even come close to it.


Be it joining multiple datasets , aggregation , null handling , filtering , data cleaning , windowing, complex derivatives etc.

It is so easy to perform data Wrangling using SQL given that you understand how it works.

I know many people who are good in python and always used to use python for all data wrangling operations mainly using pandas.

But after I showed them some magic with SQL they just fell in love with it. Some magic involves :

1- sum with case when
2- window functions
3- rolling aggregations
4- join using between clauses etc

What is your favourite tool for data wrangling?

Want to experience SQL magic ? Join my SQL zero to hero data analytics course to learn the art of SQL and sky rocket your data analytics journey.

Link to register in the comments section.

#sql #analytics

Best practices for writing SQL queries:


1- Write SQL keywords in capital letters.

2- Use table aliases with columns when you are joining multiple tables.

3- Never use select *, always mention list of columns in select clause before deployment to production.

4- Add useful comments wherever you write complex logic. Avoid too many comments.

5- Use joins instead of subqueries when possible for better performance.

6- Create CTEs instead of multiple sub queries , it will make your query easy to read.

7- Join tables using JOIN keywords instead of writing join condition in where clause for better readability.

8- Never use order by in sub queries , It will unnecessary increase runtime.

9- If you know there are no duplicates in 2 tables, use UNION ALL instead of UNION for better performance.

Anything else you want to add?

I talk about SQL, Tableau and data analytics on my youtube channel. Checkout the link in the comments section.

#dataanalytics #sql #bestpractices

You know SQL and want to learn Pandas ?


Pandas are one of the most powerful and commonly used Python library in the field of data analytics and data engineering.

It can be used for data wrangling, to read data from multiple sources ( CSV, json, databases etc..)
Various machine learning libraries support direct use of pandas.

And it has many more use cases that I cannot tell you in a post.

Good thing is pandas dataframes look similiar to a SQL table. Just like it has columns, rows and it becomes easy to understand it if you know SQL.

Why am I telling all this ??

Well, I have started the Pandas for data analysis series on my YouTube channel. I am explaining it alongside SQL concepts so that you learn both together 😊

Link in the comments section. Do subscribe to the channel for more content coming up on SQL, Python and data analytics.

#python #pandas #sql

Working 8-10 hours a day is still fine.






But commuting office for 3 hours everyday is not fine.


#office #wfh #productivity