Build an END-TO-END Supply Chain Analysis Project using Python perfect for Data Analyst and Data Scientist. In this complete project tutorial, you'll learn how to analyze a real-world supply chain dataset using Python, Pandas, Matplotlib, Seaborn, Scikit-Learn build a machine learning model and create a professional report. This is the EXACT type of project that gets noticed by recruiters. ⏰ TIMESTAMPS: 00:00 - Why Supply Chain Project? 00:30 - What is Supply Chain? 01:05 - Understanding Business Problem 03:46 - Setting Up Notebook 04:41 - Data Loading & First Look 05:34 - Exploratory Data Analysis 07:02 - Data Cleaning & Feature Engineering 13:15 - Solving Research Questions 22:31 - Bottleneck detection 25:22 - Root Cause Analysis 29:00 - Time Series Analysis 32:27 - Machine Learning Modeling 38:12 - Business Insights & Recommendations About this project: This supply chain analysis project demonstrates how data analysts solve real business problems. We use Python libraries like Pandas for data manipulation, Matplotlib and Seaborn for visualization, apply EDA techniques to derive actionable insights and build machine learning model using scikit-learn to identify high risk products from supply chain data. Whether you're a beginner data analyst or data scientist, college student preparing for placements, or a working professional looking to switch to data analytics, this project will strengthen your portfolio. 📂 Resources & Career Support (Video resources) Dataset, Code, Report: https://topmate.io/ayushi_mishra/2052119 Free Dataset: https://topmate.io/ayushi_mishra/2052121 - All tech resources (Guides, eBooks, Projects): https://topmate.io/ayushi_mishra - 7+ Portfolio-Ready Projects: https://topmate.io/ayushi_mishra/770872?utm_source=public_profile&utm_campaign=ayushi_mishra - Job Prep & Interview Secrets: https://topmate.io/ayushi_mishra/page/62xps5j5IH - Book a 1:1 Strategy Call (Resume & LinkedIn): https://topmate.io/ayushi_mishra/133733 🔗 Stay Connected - LinkedIn: https://www.linkedin.com/in/ayushi-mishra-30813b174 - Instagram: https://www.instagram.com/techie.data/ 🔥 RECOMMENDED VIDEOS: 👉 Complete Data Cleaning (Python): https://youtu.be/ZX8vmcSTCrc 👉 Machine Learning Full Course: https://youtu.be/RAniuQEl10s 👉 Statistics Full Course: https://youtu.be/S7LvZZNq4ys 👉 How to upload any Project on Github using Git Commands: https://youtu.be/_x-ripC0_LI 👉Master EDA: https://youtu.be/YAWEU0oADCk #dataanalytics #python
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Hello ayushi mam, As you said demand forecasting analysis project please make it as soon as possible. I'm really excited and waiting for this project.
Could you create more project-based videos that genuinely add value to a resume? There’s a lot of confusion in the market about what actually makes an impact.”
:( its not free
Power Bi for this project ?
Supply chain is a basic accounting concept ☺️
Madam please ek bar scratch se ML learning ka Playlist bana dijiye. beginner to advanced level tak .
Hi ayushi, good explanation, but little bit fast and why you are combining 4.5 code at once ... It would be easy for us if you make separate code for each
Ayushi, im forgetting everything im studying
*Is there a need to create a Power BI dashboard for this as well?*
I just completed your vendor performance and was looking for scm topics, this was divine timing 😄
Thank You , This Video Help me a lot
thankyou very much for dataset 🙌🙌🙌🙌
Thankyou so much ❤❤❤❤
Thanks for being so considerate about your students, efforts appreciated, also please make further projects which you mentioned
"Order Processing Time" is same as 'Days for shipping (real)' except where the difference between shipping date timestamp and order date timestamp is less than 24hrs, in that case the 'dt.days' function makes it as 0 while 'Days for shipping (real)' shows it as 1. Hence you don't need to make another column. Thus, we don't need the 'Delay' column and 'Is_Delayed' column is just 'Late_delivery_risk' (You're getting a difference in value counts only because of the calculation difference mentioned earlier). Basically which means all data related to order processing already exists; what does not exist is data related to actual delivery. According to my view, the dataset tells nothing about acutal delivery time and all, that's why the column is named 'Late_delivery_risk' because if the shipment is late the order is at risk for a late delivery. You being a content creator who is followed by so many (including me) should be more conscious I believe. Thank You for your contents !
Please, make more projects on Supply Chain!
mam need A/B TESTING projects can u plz make that one
Mam Please make an end-to-end project on financial analysis
add more projects on financial Analytics, HR Analytics
Just few days ago completed your vendor analysis project .... Took almost 15 days to completed as errors were coming continuosly but finally made it .... And now this project and now when I followed your tutorial minimal error this time ... Thank you