Mohamed Alwedaa
Data Analyst | Power BI | SQL | Business Intelligence | Systems & Database Solutions
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Zinn Hub에서 검증된 기술
인증된 ZinnerMohamed Alwedaa는 Zinn Hub에 자신의 기술을 입증하고 작업 증거를 제공했습니다. 모든 검증된 Zinner는 실습 품질 보증 검토를 통과하므로 안심하고 고용할 수 있습니다.
🛡️ October 2026부터 인증됨
정보
I am a Data Analyst and Business Intelligence professional with a technical background spanning data analytics, database design, enterprise software development, and reporting solutions.
I help clients turn raw, fragmented data into structured, reliable information — ready for reporting, performance monitoring, and confident decision-making. My core tools include Power BI, SQL, Microsoft Excel, Tableau, Python, SQL Server, and Oracle.
For Power BI projects, I can support the full workflow from data preparation to final dashboard delivery. This includes cleaning and transforming data with Power Query, building structured data models, creating KPI measures and DAX calculations, designing interactive dashboards, and presenting results in a clear business-focused format. I have practical experience building multi-page analytical dashboards using dimensional modelling and Star Schema principles.
My portfolio includes a strategic Power BI analysis of the Saudi energy market, a Tableau-based analysis of Canada's energy transition, and a database-driven financial and accounting management system for schools built with and SQL Server. These projects reflect hands-on experience across the energy, finance, and education sectors, spanning reporting, database design, and operational software development.
I also developed a modular Python-based V2G Digital Twin and grid-flexibility simulation framework for studying large-scale EV-grid coordination. The work includes stochastic modelling, Monte Carlo simulation, transformer thermal modelling, scenario analysis, and decision-support workflows. I documented the methodology in a technical research note published on Zenodo with DOI 10.5281/zenodo.21400746.
My background also includes enterprise software and database solutions. I have translated business requirements into technical specifications, designed relational databases, developed database-driven applications, supported testing and deployment, troubleshot application and data issues, and worked across the full software development lifecycle.
I hold professional certificates in Microsoft Power BI Data Analysis and Google Data Analytics, alongside training in Oracle Database Administration. I also completed the AWS Cloud Solutions Architect Professional Certificate program, which complements my data and systems background and informs how I approach cloud-hosted data services and modern application architecture.
I can assist with projects involving:
• Power BI dashboards and KPI reporting
• Data cleaning, transformation, and analysis
• SQL queries and database reporting
• Excel analysis and reporting
• Business intelligence and data visualisation
• Database design and structured data models
• Requirements analysis and technical documentation
• Python-based data processing, modelling, and simulation workflows
For smaller, well-scoped dashboard or reporting tasks, delivery is typically within a few days, subject to data quality and the agreed scope of work. For larger projects, I prefer to agree on clear milestones, deliverables, and scope before starting.
I provide handover notes and support post-delivery adjustments to ensure the final solution is understandable, maintainable, and practical to use.
I am available for short analytical tasks and longer-term projects across reporting, database design, business intelligence, and data-focused software work.
I am based in Cairo and can work flexibly across buyer time zones for milestone-based and ongoing projects.
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포트폴리오
Canada Energy Transition Analysis — Tableau & Data Analytics
Developed a data analysis and visualisation project examining Canada’s energy transition across the period 2008–2025. The project combined energy, emissions, population, economic, and renewable-energy indicators to evaluate long-term trends in greenhouse gas emissions, emissions intensity, emissions per capita, and renewable-energy production. Data preparation and analysis were completed using Excel and R, followed by the development of interactive Tableau visualisations to communicate trends and comparisons clearly. The project demonstrates practical experience in data cleaning, transformation, exploratory analysis, KPI development, trend analysis, and dashboard-based storytelling.
School Financial & Accounting Management System — VB.NET & SQL Server
Designed and developed a database-driven financial and accounting management system for schools using VB.NET and SQL Server. The system was built to support day-to-day financial operations, structured data entry, transaction management, reporting, and administrative workflows. The project involved requirements analysis, relational database design, application development, business logic implementation, reporting, testing, troubleshooting, and user support. It demonstrates end-to-end experience across the software development lifecycle, with particular strengths in database architecture, enterprise application development, financial data management, and operational reporting.
V2G Digital Twin & Grid Flexibility Simulation — Python
Developed a modular Python-based simulation framework for studying large-scale Vehicle-to-Grid (V2G) coordination and distribution-level grid flexibility. The project models approximately 1 million electric vehicles across more than 60,000 distribution transformers using stochastic EV behaviour, Monte Carlo simulation, transformer thermal modelling, and scenario-based dispatch logic. The framework is designed around modular software components so that market assumptions, EV behaviour, network conditions, and dispatch strategies can be changed independently without redesigning the full system. Key areas covered include: • Python-based simulation and data processing • Stochastic and probabilistic modelling • Monte Carlo simulation • V2G and Virtual Power Plant coordination • Transformer thermal modelling • Scenario analysis and decision-support • Modular software architecture • Grid flexibility assessment The project uses synthetic and statistically representative network data where proprietary utility topology is unavailable, with a clear distinction between simulation results and real-world operational validation. An interactive architecture explorer and published research documentation are available as supporting evidence.
