Ahmed – PowerBI, Pandas, SQL

A hotel franchise operating 40 properties across five countries required an analytical reporting dashboard to enable data-driven financial decision-making; the project integrated, transformed, and presented data from 10+ sources to monitor KPIs, performance, and operations.

• Led end-to-end design and deployment of a Microsoft Fabric analytics platform, delivering an enterprise-grade unified analytics environment integrating data from 40+ hotel systems across 5 countries, reducing data fragmentation by 70% and improving reporting efficiency;
• Established a scalable medallion architecture (Bronze–Silver–Gold) enabling automated ingestion and transformation, resulting in a 50% reduction in manual data preparation for BI teams;
• Designed semantic models in Fabric for enterprise business intelligence needs, building reusable models (DIM/FACT) covering reservations, occupancy, guest profile, F&B, revenue, and loyalty data—supporting enterprise-wide Power BI reporting and reducing duplicated effort across teams;
• Led migration from legacy on-premise systems to Microsoft Fabric, retiring three legacy databases and unified them within Fabric’s OneLake, reducing infrastructure costs by 30% and improving data refresh speeds to near real-time;
• Drove continuous improvement of the analytical ecosystem through monitoring, automation, and feedback loops, automating 80% of recurring ETL workloads using Data Factory + Fabric Pipelines, freeing analysts to focus on insights instead of data wrangling.

Referral-to-Treatment (RTT) project aimed at integrating data from multiple care points and health systems to track patient pathways longitudinally and improve visibility across the treatment lifecycle.

• Facilitated data-driven decision-making by deriving actionable insights from historical and real-time clinical data across multiple projects;
• Designed and implemented data integration strategies for projects requiring multiple medical data sources by leveraging ETL tech stack;
• Developed and maintained data warehouses to support project-specific reporting and analytics;
• Leveraged Tableau and Power BI in the creation of interactive reports and analytical dashboards for reporting indicators and monitoring KPIs;
• Created data models to reflect the specific needs of healthcare analytics;
• Conducted routine ad-hoc data analysis to address specific healthcare questions and challenges;
• Routinely optimized the performance of BI solutions to ensure real-time or near-real-time access to healthcare data.

Annual student feedback analytics initiative focused on collecting and transforming multi-source unstructured data (surveys and reviews) into dashboards and text insights (e.g., word maps) to support evidence-based academic decision-making.

• Generated meaningful insights from study records across multiple platforms by analyzing trends and patterns;
• Produced reports and visualizations to effectively communicate findings to university leadership and key stakeholders;
• Implemented data-driven strategies to improve institutional processes and outcomes;
• Routinely analyzed structured and unstructured data from student feedback across multiple platforms and conducted sentiment analysis to foster targeted interventions;
• Facilitated collaboration with other university departments and stakeholders to ensure data accuracy and consistency.

A national health data repository that aggregates de-identified patient records from electronic and paper-based systems across facilities, transmitted via HL7-compliant XML for centralized analysis and reporting.

• Led teams in building data and analytics platforms to support nationwide digital transformation initiatives, including data warehousing, migration pipelines, data quality frameworks, and epidemic monitoring dashboards;
• Directed the electronic medical record integration program, consolidating disparate health data sources into a unified, interoperable analytics platform;
• Oversaw technical implementation and routine analysis for HIV Recency Surveillance, delivering ongoing reporting and visualizations;
• Mentored and coached a team of six analysts, setting goals and development plans across SQL, Power BI, Databricks, and Python;
• Facilitated a community of practice to design country-specific solutions and strengthen health system capabilities;
• Designed predictive analytics solutions using machine learning and optimization to identify patients at risk of disengaging from care;
• Implemented SQL-based validation frameworks to improve data ingestion reliability and overall data quality for a national repository;
• Produced large-scale HIV data reports (quarterly and semi-annual) spanning 20M+ records across multiple funding streams;
• Built clustering models to segment patients by clinical indicators (e.g., viral load, CD4), informing targeted interventions across multiple regions.