Comment “chat” to download ChatGPT desktop app!
Everyone says you need a data analytics portfolio project to get hired.
But nobody actually shows you how to build one.
So I’m going to show you the full thing using Agentic Analytics.
Agentic Analytics is where humans collaborate with AI agents to complete analyses.
The three things most data analysts struggle with when building a portfolio project is finding an interesting realistic dataset, knowing how to structure the analysis and writing up the results in GitHub that appeal to a hiring manager.
I used @chatgpt Work powered by GPT-5.6 to handle the entire pipeline end-to-end:
↳ Generated a messy synthetic dataset with real-world data quality issues
↳ Wrote the SQL queries to clean and transform the data so it was ready for analysis
↳ Wrote the Python code for the EDA to visualize the data and insights
↳ Used the SQL, Python, and charts to build a write-up in a GitHub README page
As data analysts we know the write-up and communication is the most important part of the analysis, even more so than the code. That’s the part that actually gets you hired.
ChatGPT work is different than the regular ChatGPT chatbot you’re used to. It’s an agent, which means it completes entire multi-step workflows autonomously from end to end. It can think logically and reason through difficult problems without having to switch tools and it’s powered by GPT-5.6, which is killing it when it comes to reasoning, coding, and complex tasks.
Download the ChatGPT desktop app and use Work today to build your own portfolio project for data science and analytics.
#ChatGPT_partner
Comment “chat” to download ChatGPT desktop app!
Everyone says you need a data analytics portfolio project to get hired.
But nobody actually shows you how to build one.
So I’m going to show you the full thing using Agentic Analytics.
Agentic Analytics is where humans collaborate with AI agents to complete analyses.
The three things most data analysts struggle with when building a portfolio project is finding an interesting realistic dataset, knowing how to structure the analysis and writing up the results in GitHub that appeal to a hiring manager.
I used @chatgpt Work powered by GPT-5.6 to handle the entire pipeline end-to-end:
↳ Generated a messy synthetic dataset with real-world data quality issues
↳ Wrote the SQL queries to clean and transform the data so it was ready for analysis
↳ Wrote the Python code for the EDA to visualize the data and insights
↳ Used the SQL, Python, and charts to build a write-up in a GitHub README page
As data analysts we know the write-up and communication is the most important part of the analysis, even more so than the code. That’s the part that actually gets you hired.
ChatGPT work is different than the regular ChatGPT chatbot you’re used to. It’s an agent, which means it completes entire multi-step workflows autonomously from end to end. It can think logically and reason through difficult problems without having to switch tools and it’s powered by GPT-5.6, which is killing it when it comes to reasoning, coding, and complex tasks.
Download the ChatGPT desktop app and use Work today to build your own portfolio project for data science and analytics.
#ChatGPT_partner
