Boost Sales with Advanced Python Analytics for Coffee Roasters

Boost Sales with Advanced Python Analytics for Coffee RoastersBoost Sales with Advanced Python Analytics for Coffee Roasters

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Sakshi Raut

• Apr 22

ficionado Coffee Roasters – Sales & Time-Based Performance Analysis Developed an interactive dashboard using Python (Pandas, Plotly, Streamlit) to analyze transaction-level data and uncover sales patterns across time and store locations. Identified peak hours, day-wise trends, and product performance, and provided actionable recommendations to optimize staffing, operations, and revenue.

Microsoft Excel Microsoft Power BI Data Analysis

Moez Khan

• Apr 19

Procurement Intelligence 🧠

• Scores and ranks every vendor by risk across 4 dimensions • Quantifies financial exposure tied to critical suppliers • Tracks negotiation savings by supplier and category • Flags every policy violation and traces it to the source • Measures your gap to audit compliance in real time • All insights update live with every filter selection

Data Analysis Data Engineering Data Science Microsoft Excel Microsoft Power BI

Geethasree Naguboina

pro

• Apr 22

The supplier risk matrix plotting defect rate against risk score is a really smart way to visualize procurement risk — most businesses just track spend without ever connecting it to compliance or defect patterns until something goes wrong.

The weighted risk score ranking makes it...

Johnson Wairimu

• Apr 19

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Istiak Ahmed Khan

• Apr 22

Showing regional sales performance was a great idea,

Shahd Emad

• Apr 19

I create detailed coffee sales reports that analyze performance across products, locations, and time periods. The report includes key metrics such as total sales, top-selling coffee items, revenue trends, and customer preferences. I organize the data into clear visuals and summaries to help identify business opportunities, optimize inventory, and improve overall decision-making.

Microsoft Power BI Data Analysis