Wafa Zainab

Optimized SQL and Python telemetry pipelines, improving IoMT data processing speed by 30% and reducing missing-data incidents. Engineered feature extraction workflows that boosted anomaly detection accuracy by 22% across healthcare IoT devices. Built Power BI dashboards that automated operational reporting, saving 4–6 hrs/week of manual effort for engineering teams. Designed data-quality and security validation scripts, surfacing log inconsistencies 40% faster, strengthening IoMT safety.

Cleaned, transformed, and visualized operational datasets, improving reporting accuracy by 18% for management dashboards. Automated Excel/SQL reports for weekly performance reviews, reducing preparation time from 2 hrs to <20 minutes. Analysed customer and logistics workflows, identifying 3 key inefficiencies later integrated into process improvement initiatives. Built simple predictive insights (trend/variance analysis) that supported higher-quality inventory decisions.

Developed optimized SQL queries and structured datasets, reducing financial data-processing errors by 30%. Created automated dashboards for transactional monitoring, improving reporting turnaround time by 25%. Mapped source-to-target workflows, strengthening the foundation for dbt-style transformation logic in secure architectures. Validated cloud integration flows (DB2/MySQL to multi-cloud), ensuring secure and encrypted data movement.