15. Final Project: Blinkit Maharashtra Monthly Report
15.1 Project Brief and Data
Brief. Blinkit and Amazon Now (fictional data) want one monthly report for Ganeshotsav month, September 2026, covering the six cities. The report is for Ravindra Bagale (regional lead) and the six city managers. It must answer:
- What were Net Sales, Delivered Orders, AOV and Cancellation Rate for the month?
- Which city and which area contributed most? Which is below target?
- How did daily sales move during Ganeshotsav (festival spike expected from 14-09-2026, the start of the festival in this fictional data)?
- Which categories (Dairy, Fruits, Sweets, Pooja Items, Snacks…) sold most per city?
- Are deliveries within the 12-minute promise in every city?
Input files (you create them with fictional rows):
| File / sheet | Rows (suggested) | Columns |
|---|---|---|
Raw_Orders |
300–500 | Order ID, Order Date, City, Area, Store ID, Product, Qty, Amount, Delivery Mins, Status, Customer, Phone |
Stores |
12 (2 per city) | Store ID, Platform, City, Area, City Manager, Manager Email |
Products |
25 | Product, Category, Unit Price |
Targets |
6 | City, Monthly Target |
Use only these people: Ravindra Bagale, Shraddha Bagale, Ruhi Bagale, Shahrukh, Amir, Salman, Zoya, Ravina, Raja, Rani, with @example.com e-mails. Areas: Pune (Kothrud, Hinjewadi, Baner, Hadapsar, Wakad), Nashik (College Road, Gangapur Road), Nagpur (Dharampeth, Sitabuldi), Kolhapur (Rajarampuri, Tarabai Park), Solapur (Hotgi Road, Murarji Peth), Sambhaji Nagar (CIDCO, Nirala Bazar).
Steps to prepare the raw data (deliberately messy)
- Type or generate the rows; then damage about 10% of them on purpose: extra spaces, "pune/PUNE", "Aurangabad" for Sambhaji Nagar, text amounts like "Rs. 450", US-style dates, 5–8 duplicate rows, a few blank Delivery Mins, phone numbers with +91 and spaces.
- Keep a copy of this untouched sheet as
Raw_Ordersand never edit it. - Write the five questions above on a
Notessheet with KPI definitions (Module 13.1).
Worked example – a few raw rows.
| Order ID | Order Date | City | Amount | Status |
|---|---|---|---|---|
| blk-9001 | 14-09-2026 | pune | Rs. 450 | delivered |
| BLK-9002 | 09/14/2026 | Aurangabad | 1,299 | Delivered |
| BLK-9001 | 14-09-2026 | pune | Rs. 450 | delivered |
Ravindra Bagale's Tip
Many students take already-clean data for their project – then in the interview they have no answer to "what challenges did you face?" Deliberately create messy data and write down every problem and its fix on a Notes sheet. That is the real "story" of your project.
Ravindra Bagale's Tip – मराठी
बरेच students project साठी आधीच clean data घेतात – मग interview मध्ये "what challenges did you face?" ला काहीच उत्तर नसतं. मुद्दाम messy data बनवा आणि प्रत्येक problem आणि त्याचा fix Notes sheet वर लिहून ठेवा. हीच तुमच्या project ची खरी "story" असते.
Ravindra Bagale's Tip – हिंदी
बहुत से students project के लिए पहले से clean data ले लेते हैं – फिर interview में "what challenges did you face?" का कोई जवाब नहीं होता. जानबूझकर messy data बनाओ और हर problem और उसका fix Notes sheet पर लिखकर रखो. यही तुम्हारे project की असली "story" होती है.
Practice task
Create the four input sheets with fictional data for September 2026 and introduce at least eight different data-quality problems into Raw_Orders. List each problem on the Notes sheet.