Data & business analytics
Project 02 · Specialty coffee
Sales intelligence
Sales, margin, targets, customers, and regions for a specialty coffee brand selling through four channels: B2B distribution, own stores, e-commerce, and marketplaces.
Client: Alma Andina · fictitious, simulated data
Net sales (COP)
$ 40 mil M
Orders processed
181 mil
Customers served
7.748

The challenge
Alma Andina sells through four channels and tracked each one in a separate file. Management could not tell whether growth came with margin, which products carried the business, or which reps needed help to hit target.
Python · Power Query · DAX · Power BI
Key findings
- Sales grow 33.1% year over year; e-commerce nearly doubles (+96%).
- Gross margin rises to 33.0% (+4.6 pp); subscriptions are the most profitable category.
- Discounts eat 17% of potential margin; the biggest is with retail chains (15%).
Capabilities shown
- Time intelligence (YTD, prior year, 3-month rolling)
- Dynamic ABC / Pareto analysis
- Targets by rep with TREATAS
- Customer cohorts
Dashboard tour
7 views. Click any view to enlarge it.
Live interactive dashboard
Use the filters and the navigation menu inside the dashboard, just as a manager would.
Data & business analytics
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