Top Tweets for #dataforgechallenge
Data Forge Challenge #002
Analysed e-commerce profit & payment trends.
3 insights:
1. 5 sub-categories lose money
2. Credit Card margin 14.5% vs UPI 4.8%
3. Printers & Bookcases lead profit
Tools: Power BI
Full analysis: [https://t.co/k8x6jP4Ne8]
@bayyoo_ #dataforgechallenge
![AishatOyinda's tweet photo. Data Forge Challenge #002
Analysed e-commerce profit & payment trends.
3 insights:
1. 5 sub-categories lose money
2. Credit Card margin 14.5% vs UPI 4.8%
3. Printers & Bookcases lead profit
Tools: Power BI
Full analysis: [https://t.co/k8x6jP4Ne8]
@bayyoo_ #dataforgechallenge https://t.co/hq4ah8ElGt](https://pbs.twimg.com/media/HTnn7cqXoAAsvFa.jpg)
Data Forge Challenge #002
I analysed an e-commerce sales dataset
Full details of my findings are here : https://t.co/hDJeEtxEWi
@bayyoo_ #dataforgechallenge
My Power BI Insights Dashboard π
I didn't just want charts.
I want findings.
So I built it around 3 pillars:
INSIGHT - What's happening?
EVIDENCE - What does the data say?
IMPACT- Why does it matter?
Insight Idea from @PeterFatd1
Dataset from @bayyoo_
#dataforgechallenge
Data Forge Challenge #002
I analysed an e-commerce sales dataset to investigate product profitability and payment trends.
Here are 3 key insights I discoved π:
@bayyoo_ #dataforgechallenge
Data Forge Weekly Challenge 002 π
Open to everyone.
Everything you need is here β the dataset + submission guidelines ππ½
https://t.co/3XePCjAQq3
Deadline: 28th September
Read the guidelines before submitting.
π
#DataForgeChallenge
Data Forge Challenge #002
I analysed an e-commerce sales dataset to investigate product profitability and payment trends.
COD is the most frequently use payment method
Tools: Excel
π @bayyoo_ @silverpenydr
#dataforgechallenge
Hopped on Data Forge Challenge #02 this afternoon and this is what I came up with! π
Built an E-Commerce Sales & Profitability dashboard in Power BI.
Still learning, so I'm open to feedback and suggestions. Also would love to connect with others
@bayyoo_
#DataForgeChallenge
Data Forge Weekly Challenge 002 π
Open to everyone.
Everything you need is here β the dataset + submission guidelines ππ½
https://t.co/3XePCjAQq3
Deadline: 28th September
Read the guidelines before submitting.
π
#DataForgeChallenge
Why are 45.5% of food deliveries severely delayed?
Itβs easy to blame rain or traffic, but the numbers tell a very different story.
Here is my analysis and executive dashboard for SwiftRoute Logistics for the #dataforgechallenge: π§΅π
Good Evening Everyone
My first Analysis as a beginner still not perfect yet but hoping to learn more.
I hopped on the weekly challenge by @bayyoo_
Attached below are the questions asked and the result I got from my analysis.
#dataforgechallenge @bayyoo_
I did an analysis on a Food delivery route dataset , This dataset consist of the deliveries made between January 1st -4th.
This project uncovers performance patterns across different delivery modes,e.t.c.
Full Analysis : https://t.co/tVOdO08Rqy
#dataforgechallenge
I analysed a food delivery dataset to investigate the factors affecting delivery efficiency.
Full analysis: https://t.co/k9xgncUO5Y
#dataforgechallenge
Data Forge Weekly Challenge 001 π
Open to everyone.
Everything you need is here β the dataset + submission guidelines ππ½
https://t.co/hkVU7eiLyw
Deadline: 20th September
Read the guidelines before submitting.
Letβs see what you come up with. ππ
#DataForgeChallenge
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