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Developed an end-to-end Customer Churn Analysis project to identify customers who are likely to leave a company. The project combines SQL, Python, Pandas, and exploratory data analysis (EDA) to uncover business insights that can help improve customer retention and reduce churn.
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A business can have hundreds of enquiries every month and still struggle to grow.
Why?
Because enquiries end up in WhatsApp chats, emails, notebooks, and spreadsheets. Follow ups get forgotten, team members don't know who's handling what, and potential customers quietly disappear.
The issue usually isn't a lack of leads, it's a lack of a system.
My Solution
I'd build a simple customer management platform that keeps everything in one place.
Features would include:
Automatic lead capture
Centralised customer records
Follow up reminders
Team task assignment
Real-time sales pipeline
Analytics to track performance
Instead of chasing information, the team can focus on building relationships and closing deals.
Technology should remove friction, not create more of it.
If you were running this business, what feature would be essential for you?
#ProductDesign #FullStackDevelopment #CRM #BusinessAutomation #SaaS #WebDevelopment #Startup #CustomerExperience #BuildInPublic #Contra
Great Dev🧠 💯 🔥
Your Supabase app is working… but your database is still exposed? 🔐
One mistake I see developers make is setting up authentication and forgetting about Row Level Security (RLS).
If you're using Supabase, don't just create your tables and move on.
Make sure you:
✅ Enable RLS on your tables
✅ Create policies for who can read data
✅ Create policies for who can insert or update data
✅ Never expose sensitive service keys in the frontend
✅ Test your policies with different user accounts
Authentication tells you who the user is. RLS helps control what they can access.
Have you ever had an RLS policy block something that should have worked? 👇
Impressive, thanks for the tips love ❤️
Netflix Movies Analysis Dashboard using Power BI
Project Overview
Interactive Power BI dashboard analyzing Netflix movie trends, popularity, ratings, genres, and language distribution.
KPIs
Total Movies
Total Votes
Total Popularity
Average Rating
Dashboard Features
Top 10 Movies by Popularity
Release Year Trend
Movies Distribution by Language
Genre Analysis
Popularity vs Vote Average
Tools Used
Power BI
Power Query
DAX
Data Modeling
