6 parts to a ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐'s job.
AI is already taking some of them.
Not all.
Some.
It will expose weak ones.
https://www.linkedin.com/feed/update/urn:li:share:7492169595961688064/
AI is already taking some of them.
Not all.
Some.
It will expose weak ones.
https://www.linkedin.com/feed/update/urn:li:share:7492169595961688064/
LinkedIn
๐๐ ๐ฝ๐ฟ๐ผ๐ฏ๐ฎ๐ฏ๐น๐ ๐๐ผ๐ป'๐ ๐ฟ๐ฒ๐ฝ๐น๐ฎ๐ฐ๐ฒ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐๐.
It will expose weak ones.
Nobody is saying this clearly enough.
6 parts to a ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐'sโฆ
It will expose weak ones.
Nobody is saying this clearly enough.
6 parts to a ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐'sโฆ
๐๐ ๐ฝ๐ฟ๐ผ๐ฏ๐ฎ๐ฏ๐น๐ ๐๐ผ๐ป'๐ ๐ฟ๐ฒ๐ฝ๐น๐ฎ๐ฐ๐ฒ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐๐.
It will expose weak ones.
Nobody is saying this clearly enough.
6 parts to a ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐'s job.
AI is already taking some of them.
Not all.
Some.
Know the difference before it costs you.
โ = AI handles this nowโฆ
It will expose weak ones.
Nobody is saying this clearly enough.
6 parts to a ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐'s job.
AI is already taking some of them.
Not all.
Some.
Know the difference before it costs you.
โ = AI handles this nowโฆ
โYour resume says you know SQL.
But can you actually think in SQL?โ
This can become a technical + career post.
Give a simple example:
https://www.linkedin.com/feed/update/urn:li:share:7493510053992439809/
But can you actually think in SQL?โ
This can become a technical + career post.
Give a simple example:
https://www.linkedin.com/feed/update/urn:li:share:7493510053992439809/
LinkedIn
"๐ฌ๐ผ๐๐ฟ ๐ฟ๐ฒ๐๐๐บ๐ฒ ๐๐ฎ๐๐ ๐๐ผ๐ ๐ธ๐ป๐ผ๐ ๐ฆ๐ค๐."
But can you actually think in SQL?
Company revenue dropped last month.
A beginner might immediatelyโฆ
But can you actually think in SQL?
Company revenue dropped last month.
A beginner might immediatelyโฆ
"๐ฌ๐ผ๐๐ฟ ๐ฟ๐ฒ๐๐๐บ๐ฒ ๐๐ฎ๐๐ ๐๐ผ๐ ๐ธ๐ป๐ผ๐ ๐ฆ๐ค๐."
But can you actually think in SQL?
Company revenue dropped last month.
A beginner might immediately write a query.
A stronger analyst first asks:
- Is revenue actually down, or is the dataset incomplete?
- Which productsโฆ
But can you actually think in SQL?
Company revenue dropped last month.
A beginner might immediately write a query.
A stronger analyst first asks:
- Is revenue actually down, or is the dataset incomplete?
- Which productsโฆ
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐e๐ฟ:
You have 2 minutes to solve this Excel problem.
You have the following data:
Employee Department Salary
John IT 75,000
Sarah HR 60,000
Mike IT 82,000
David Finance 90,000
Alice HR 65,000
How would you find the second highest salary in the IT department?
๐ ๐ฒ: Challenge accepted! ๐ช
=LARGE(FILTER(C2:C6,B2:B6="IT"),2)
๐ก Explanation:
This formula combines FILTER() and LARGE() to find the second highest salary within a specific department.
- FILTER(C2:C6,B2:B6="IT") returns only salaries from the IT department.
- LARGE(...,2) returns the second largest value from those salaries.
The result is 75,000.
This challenge tests your understanding of: โ FILTER()
โ LARGE()
โ Conditional Filtering
โ Combining Excel Functions
๐ Bonus (Without FILTER)
For older Excel versions, you can use:
=AGGREGATE(14,6,C2:C6/(B2:B6="IT"),2)
Here:
14 represents LARGE.
6 ignores errors.
B2:B6="IT" filters the calculation to the IT department.
2 returns the second largest value.
โค๏ธ React with โค๏ธ for more Excel interview challenges!
You have 2 minutes to solve this Excel problem.
You have the following data:
Employee Department Salary
John IT 75,000
Sarah HR 60,000
Mike IT 82,000
David Finance 90,000
Alice HR 65,000
How would you find the second highest salary in the IT department?
๐ ๐ฒ: Challenge accepted! ๐ช
=LARGE(FILTER(C2:C6,B2:B6="IT"),2)
๐ก Explanation:
This formula combines FILTER() and LARGE() to find the second highest salary within a specific department.
- FILTER(C2:C6,B2:B6="IT") returns only salaries from the IT department.
- LARGE(...,2) returns the second largest value from those salaries.
The result is 75,000.
This challenge tests your understanding of: โ FILTER()
โ LARGE()
โ Conditional Filtering
โ Combining Excel Functions
๐ Bonus (Without FILTER)
For older Excel versions, you can use:
=AGGREGATE(14,6,C2:C6/(B2:B6="IT"),2)
Here:
14 represents LARGE.
6 ignores errors.
B2:B6="IT" filters the calculation to the IT department.
2 returns the second largest value.
โค๏ธ React with โค๏ธ for more Excel interview challenges!
Notion is hiring Software Engineer (Developer Expereince)
For 2015, 2016, 2017 grads
Location: Hyderabad
https://jobs.ashbyhq.com/notion/49bdf081-6e20-4323-8c73-6d6b19544ff5
For 2015, 2016, 2017 grads
Location: Hyderabad
https://jobs.ashbyhq.com/notion/49bdf081-6e20-4323-8c73-6d6b19544ff5
Ashbyhq
Software Engineer, Developer Experience
WHO WE ARE
Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearerโฆ
Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearerโฆ
Arcadis is hiring Graduate Engineer
For 2022, 2023, 2024, 2025 grads
Location: Bangalore
https://jobs.arcadis.com/careers/job/563671532643966?domain=arcadis.com
For 2022, 2023, 2024, 2025 grads
Location: Bangalore
https://jobs.arcadis.com/careers/job/563671532643966?domain=arcadis.com
๐ป๐ด๐ป. $๐ฎ.๐ฏ ๐ฏ๐ถ๐น๐น๐ถ๐ผ๐ป ๐๐ฎ๐น๐๐ฎ๐๐ถ๐ผ๐ป. ๐ด๐ฑ,๐ฌ๐ฌ๐ฌ+ ๐๐ถ๐๐๐๐ฏ ๐๐๐ฎ๐ฟ๐.
Still not on your learning list?
High demand. Low competition.
That's the window right now.
And it's closing faster than most people realize.
๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ป๐ด๐ป?
https://www.linkedin.com/feed/update/urn:li:share:7495692689452007424/
Still not on your learning list?
High demand. Low competition.
That's the window right now.
And it's closing faster than most people realize.
๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ป๐ด๐ป?
https://www.linkedin.com/feed/update/urn:li:share:7495692689452007424/
LinkedIn
๐ป๐ด๐ป. $๐ฎ.๐ฏ ๐ฏ๐ถ๐น๐น๐ถ๐ผ๐ป ๐๐ฎ๐น๐๐ฎ๐๐ถ๐ผ๐ป. ๐ด๐ฑ,๐ฌ๐ฌ๐ฌ+ ๐๐ถ๐๐๐๐ฏ ๐๐๐ฎ๐ฟ๐.
Still not on your learning list?
High demand. Low competition.
That's the windowโฆ
Still not on your learning list?
High demand. Low competition.
That's the windowโฆ
๐ป๐ด๐ป. $๐ฎ.๐ฏ ๐ฏ๐ถ๐น๐น๐ถ๐ผ๐ป ๐๐ฎ๐น๐๐ฎ๐๐ถ๐ผ๐ป. ๐ด๐ฑ,๐ฌ๐ฌ๐ฌ+ ๐๐ถ๐๐๐๐ฏ ๐๐๐ฎ๐ฟ๐.
Still not on your learning list?
High demand. Low competition.
That's the window right now.
And it's closing faster than most people realize.
๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ป๐ด๐ป?
Open-source workflow automation tool.
Drag. Drop.โฆ
Still not on your learning list?
High demand. Low competition.
That's the window right now.
And it's closing faster than most people realize.
๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ป๐ด๐ป?
Open-source workflow automation tool.
Drag. Drop.โฆ
A recruiter sees SQL, Power BI, Python on your resume.
Still rejects you.
Because tools are not the job.
Analytical thinking is.
And most freshers never learn the difference.
https://www.linkedin.com/feed/update/urn:li:ugcPost:7498584894227410944/
Still rejects you.
Because tools are not the job.
Analytical thinking is.
And most freshers never learn the difference.
https://www.linkedin.com/feed/update/urn:li:ugcPost:7498584894227410944/
LinkedIn
Data Analyst Notes | Rupnath Shaw
A recruiter sees SQL, Power BI, Python on your resume.
Still rejects you.
Because tools are not the job.
Analytical thinking is.
And most freshers never learn the difference.
Here's what separates someone who knows 5 tools
from someone who is actuallyโฆ
Still rejects you.
Because tools are not the job.
Analytical thinking is.
And most freshers never learn the difference.
Here's what separates someone who knows 5 tools
from someone who is actuallyโฆ
A fresher DM'd me this week.
"6 months in. Still no clarity."
He had tried Python. Tableau. R. SQL.
All at once.
No depth anywhere.
I gave him one answer:
The order matters more than the tools.
Here's what to actually prioritize first:
https://www.linkedin.com/feed/update/urn:li:share:7499353779415302144/
"6 months in. Still no clarity."
He had tried Python. Tableau. R. SQL.
All at once.
No depth anywhere.
I gave him one answer:
The order matters more than the tools.
Here's what to actually prioritize first:
https://www.linkedin.com/feed/update/urn:li:share:7499353779415302144/
LinkedIn
A fresher DM'd me this week.
"6 months in. Still no clarity."
He had tried Python. Tableau. R. SQL.
All at once.
No depth anywhere.โฆ
"6 months in. Still no clarity."
He had tried Python. Tableau. R. SQL.
All at once.
No depth anywhere.โฆ
A fresher DM'd me this week.
"6 months in. Still no clarity."
He had tried Python. Tableau. R. SQL.
All at once.
No depth anywhere.
I gave him one answer:
The order matters more than the tools.
Here's what to actually prioritize first:
โ ๐๐ ๐ฐ๐ฒ๐น. Mostโฆ
"6 months in. Still no clarity."
He had tried Python. Tableau. R. SQL.
All at once.
No depth anywhere.
I gave him one answer:
The order matters more than the tools.
Here's what to actually prioritize first:
โ ๐๐ ๐ฐ๐ฒ๐น. Mostโฆ
I was reviewing a fresher's portfolio last week.
Beautiful dashboard. Zero question.
That's the mistake I keep seeing.
And it quietly kills your chances in every interview.
Here's what the pattern looks like:
https://www.linkedin.com/feed/update/urn:li:share:7500057785079001088/
Beautiful dashboard. Zero question.
That's the mistake I keep seeing.
And it quietly kills your chances in every interview.
Here's what the pattern looks like:
https://www.linkedin.com/feed/update/urn:li:share:7500057785079001088/
LinkedIn
I was reviewing a fresher's portfolio last week.
Beautiful dashboard. Zero question.
That's the mistake I keep seeing.
And itโฆ
Beautiful dashboard. Zero question.
That's the mistake I keep seeing.
And itโฆ
I was reviewing a fresher's portfolio last week.
Beautiful dashboard. Zero question.
That's the mistake I keep seeing.
And it quietly kills your chances in every interview.
Here's what the pattern looks like:
Open Power BI.
Pick a Kaggle dataset.
Spendโฆ
Beautiful dashboard. Zero question.
That's the mistake I keep seeing.
And it quietly kills your chances in every interview.
Here's what the pattern looks like:
Open Power BI.
Pick a Kaggle dataset.
Spendโฆ