Baraa Alashi

Developed a predictive analytics model using IBM SPSS Modeler to analyze automotive sensor data and identify patterns associated with vehicle performance and potential failures. Cleaned, prepared, and transformed raw sensor datasets, then applied data mining techniques to build classification/predictive models. Evaluated model performance using accuracy metrics and validation techniques to improve reliability. The project demonstrated how sensor-driven insights can support predictive maintenance and early fault detection in automotive systems. Done for an assignment in my data mining course.

Prototype system leveraging Rovo to analyze and classify Jira tickets based on task type, priority, and required skills. Designed prompt workflows to match tasks with team members by role and availability, integrating with Jira APIs to simulate automated assignment and improve workflow efficiency.

Market analysis of global FMCG brands — Coca-Cola, Nivea, Lay's. Built a complete business case using PivotTables, VLOOKUP, and NRM principles to uncover revenue growth opportunities and forecast market shifts.

Queried a movie rental database to uncover customer preferences and sales trends. Used OLAP extensions for multidimensional insight generation.

Pulled U.S. Census data via API, mapped demographic patterns, and calculated segregation indices to surface population-level insights.

Built an interactive dashboard for HealthStat to analyze hospital LOS, cost drivers, and care efficiency across facilities.

End-to-end churn dashboard for a telecom company. Identified key churn drivers and designed reports to guide retention strategy.