Alliyu Ajagun

8,800 sales opportunities scattered across 4 disconnected exports, with no visibility into what actually drives revenue by sector or region.

Modeled a star schema in Power BI with custom DAX measures and built a two-page executive dashboard.

Found that revenue gaps come from opportunity volume, not win rate - reframing the fix from sales coaching to pipeline generation.

Airbnb investors had no data-backed answer for where to invest, which hosts or room types perform best, or which hosts to prioritize for onboarding.

Cleaned and modeled listings data in SQL Server, then visualized findings in Power BI.

Identified the top 4 highest-ROI neighborhoods and a specific, underused onboarding segment - part-time hosts averaging 112 available days a year.

Mobile brands in Nigeria had no reliable read on what actually drives a purchase decision, or how brand loyalty and switching intent break down.

Designed and ran a 162-respondent survey, analyzed it in SQL across 7 business questions, and modeled a star schema in Power BI.

Found durability outranks price as the top purchase driver, and that 53.1% of consumers intend to switch brands - directly challenging assumptions brands make about this market.

Hospital leadership had 5 disconnected data sources and no unified view of what drove revenue or where cash flow was breaking down.

Merged all 5 datasets in Python (pandas), ran a full exploratory analysis, and quantified revenue by treatment, payment status, and department.

Found 68.5% of billed revenue was stuck in Failed or Pending status - a bigger problem than any single treatment or department underperforming.

IT security leaders had no clear, data-driven view of whether cyber-defense capabilities were keeping pace with rising threats.

Modeled the dataset as a star schema in Power BI and analyzed incident volume, financial loss, attack type, and response time by country.

Found threat volume and financial cost are rising faster than response times are improving - average response time sits at 36.5 hours.

Nigeria's PAYE tax is progressive across 6 bands with multiple reliefs, and most people estimate their tax with a flat-rate guess or opaque payroll software.

Built a fully formula-driven Excel model - zero macros - with fully visible, auditable, band-by-band calculation logic.

Delivers a transparent, self-serve tax breakdown showing exactly how each income band and relief affects take-home pay.