Data Analyst | BI · Research · Applied Analytics
Power BI & Tableau Projects
This page presents BI and data visualization projects across urban mobility, energy systems and e-commerce.
The flagship project — E-Scooter Safety Analytics — is a multi-phase longitudinal study combining crash data, GIS, surveys and enforcement records into an interactive Power BI system for decision-makers. It is followed by independent projects demonstrating analytical work across different domains and tools.
A multi-phase longitudinal study integrating 12.5 years of national crash data (CBS Israel), municipal GIS layers, Tel Aviv rider surveys, and enforcement records into a series of interactive Power BI dashboards for the municipality.
Central analytical contribution: systematic analysis of crash volume and severity as two independent dimensions across time, location, demographics, road conditions and crash type simultaneously — revealing contrasting patterns that single-indicator analysis cannot detect.
E-Scooter Safety Analytics · Israel & Tel Aviv (2013–2025)
A Longitudinal Multi-Phase Research Project
FLAGSHIP PROJECT · Power BI · SQL · Python · QGIS · 4 Phases · Presented at Technion ISTRC 2026
Phase 1 Israel — All Road Crashes · CBS 2013–2023 · National overview, all vehicle types
Phase 2 Tel Aviv Micromobility · CBS 2023–Aug 2024 · Benchmarking against Israel national data
Phase 3 Tel Aviv E-Scooters · CBS 2023–Jun 2025 · vs. other micro modes + Israel · QGIS quarters & streets
Phase 4 Tel Aviv 2013–2025 · Full integration: CBS + GIS + Surveys + Enforcement ⏳ In progress
KEY FINDINGS
· Crash volume and severity follow distinct, often opposing patterns across all dimensions — a central finding of the longitudinal analysis
· ES passengers face dramatically higher injury risk (~23% severity rate) vs. riders (~7.5%), despite being only 1.3% of those involved
· Helmet law (2021) increased compliance from ~52% to ~70%, but passenger protection remains critically low
· Official police data captures only ~5% of real solo crash events
· AI-powered features (Decomposition Tree, Key Influencers, Q&A visual) enable non-expert municipal staff to explore data independently
RESEARCH OUTPUTS FROM THIS PROJECT
Solo Crash Underreporting Study
Official data captures ~5% of real solo e-scooter crash events
Helmet Law Impact Analysis
Pre/post analysis of Israel's 2021 helmet legislation across three data sources
Presented at: ISTRC Conference, Technion, January 2026
Electricity Demand and Supply Gaps: Sub-Saharan Africa vs. Other Regions
Capstone project as part of the Hamoye Data Science Internship (Spring 2024).
Group project using Generative AI for electricity demand-supply gap forecasting.
My contribution:
· Analyzed electricity-related indicators across regions, focusing on Sub-Saharan Africa
· Identified structural patterns in demand and supply over time
· Designed new metrics to quantify the demand–supply gap as a modeling target variable
· Built Tableau dashboard to visualize regional patterns and support scenario analysis
Tools: Tableau, Python
E-Commerce Product Range Analysis
Analysis of transaction history for an online household goods store, aimed at increasing revenue through smarter product assortment.
Approach:
· Designed analytical framework to evaluate product range performance
· Identified revenue drivers, seasonal trends and underperforming categories
· Built Tableau dashboard for visual exploration of findings