In this tutorial, I will show you how to go from a raw Excel file to a fun, interactive customer dashboard using Cursor (an AI-powered code editor that you can access for free). This is the kind of project that will help you stand out from other data analyst candidates and capture the attention of hiring managers. Here’s what we will build together: Exploratory data analysis & data cleaning on an e-commerce dataset Performing a deep-dive analysis and providing business insights based on sales analysis, geographic analysis, and product performance Customer segmentation using RFM analysis A 2-page interactive Streamlit dashboard with a business overview and a customer lookup tool. Video Resources: Prompts: https://drive.google.com/file/d/1CgXLhTsEq-GgnTczqK0rkripnCwilavA/view?usp=sharing Link to dataset: https://archive.ics.uci.edu/dataset/352/online+retail Cursor: https://www.cursor.com Python Setup: This tutorial requires Python with packages like Pandas, Matplotlib, and Seaborn. The easiest way to get everything working is to install Python through Anaconda. This installs both Python and all the required packages automatically. Once installed, open Cursor and select the Python kernel that came with Anaconda. MacOS: https://youtu.be/V4riykgUS94?si=hwjPYs62u1XUhAWQ Windows: https://youtu.be/hSo1b2ITwCM?si=ZKp7ms1CAP4sMmml Additional Resources for Data Analytics: Learn Python: https://datacamp.pxf.io/Xx1qao Learn Excel Fundamentals: https://datacamp.pxf.io/9LWaQj Learn SQL for Data Analytics: https://datacamp.pxf.io/xL9DbR Learn Tableau for Data Analytics: https://datacamp.pxf.io/QjO3ex Introduction to Statistics: https://datacamp.pxf.io/xkY4gA Learn Data Analysis with ChatGPT: https://365datascience.pxf.io/bkbWgv Video Timeline: Intro 0:00 Setting up our AI Tool 2:48 Cursor Interface 6:11 Exploratory Data Analysis with AI 10:17 Data Preprocessing 12:34 Data Analysis Deep Dives 14:25 Customer Segmentation 25:21 Customer Segmentation with Cursor 27:26 Building a Data Analytics Customer Dashboard 37:03 Connect With Me: LinkedIn: https://www.linkedin.com/in/natassha-selvaraj-33430717a/ Twitter/X: https://x.com/blahblahnats
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can you please put how to make a resume for a fresher data analytics because there is no any experience for freshers so most of the hiring company is not hiring freshers
Drop a comment if you're stuck at any point in the video and I'll try to help you out!
Data Analytics has evolved each day more than expected
Im not very familiar with using AI for data analysis, and your video really helped me understand it better. Please continue sharing the latest updates and trends. It would also be helpful if you could share your journey — how you started and how you improved your skills. Looking forward to your upcoming posts sisy.
Really amazing , very interactive, learned lots from that project,, waiting for more AI generating projects.
Thanks ! Worth to watch especially 44:55 afterwards apart from performing project, which was good as well.🎉
Thank you very much Natassha for the valuable information that you have provided I don't even know about the cursor AI which you had shown nicely.😊
I would replace Cursor with Antigravity. Everything is same. Even cursor is better than Antigravity. The only reason is cursor is paid. While Antigravity gives weekly free credits include Claude opus 4.6 thinking model for free with credit limit. Which is why I would prefer Antigravity. Everything else is almost same including user interface
Excellent work. Loved it. This is one of the best for practice. My question is what if the datasets are big or some companies don't allow to download data. We have to use their database. In these types of scenarios, can we use it or not possible?
Wow! This is mind blowing
Thank you so much!!
Ai is irrefutable however business intelligence should be accompanied with wise understanding.Thanks Natassha.
Good evening Natassha, i tired to practice your video verbatim, i got stuck when i input the prompt and it didn't run the code on jupyter notebook, when i asked chat gpt, it said it was because i was using ipynb i should use .py instead. please explain better
This project is only developed by Python
I m jobless 😭 can I stay in ur house 🏡