Detail-oriented Data Analyst with expertise in SQL, Excel, Power BI, and Python, dedicated to translating complex datasets into clear, impactful insights. Skilled in data visualization, simplifying technical findings for diverse audiences, and uncovering hidden patterns beyond raw numbers. Adept at storytelling with data, crafting compelling narratives that drive informed decision-making. Experienced in designing interactive dashboards, conducting training sessions, and collaborating across teams to enhance data-driven strategies. Passionate about delivering actionable insights that bridge the gap between data and decision-makers.
This Power BI project provides an interactive analysis of Adventure Works business performance, covering sales, profit, returns, products, pricing, and customer insights. It includes executive KPIs, trend analysis, what-if scenarios, drillthrough pages, and Q&A features to support deeper exploration
This Power BI project provides an interactive financial analysis of Al Amreyah Cement, covering revenue, expenses, profitability, budget variance, balance sheet position, liquidity, and working capital. It is designed to support financial diagnosis and highlight performance gaps.
Python project for A/B testing analysis using Pandas, SQL, and statistical testing to compare CTR performance between test and control groups.
This project addresses the water crisis in Maji Ndogo through comprehensive SQL analysis. Leveraging data-driven solutions, it aims to understand water access issues, assess water quality, and propose strategies for improvement.
This project presents a complete SQL-based business analysis using the AdventureWorks database. It answers 15 key business questions covering sales performance, customer behavior, product insights, inventory analysis, and geographic performance.
This project develops a time series forecasting model to predict website traffic for TheCleverProgrammer.com. The analysis covers visitor data from June 2021 to June 2022, with the goal of understanding traffic patterns and building accurate predictions for future periods.
This project focuses on analyzing diamond prices based on their characteristics (carat, cut, color, clarity, etc.) and building a predictive model to estimate diamond prices.
The project aimed to analyze employee survey data using Microsoft Excel. The dataset included responses from employees across different departments, with varying levels of agreement/disagreement on several statements. The goal was to import, clean, analyze, and visualize the data to derive meaningful insights regarding employee satisfaction and areas for improvement within the organization.
This project aims to develop a predictive model to determine whether a patient has diabetes based on certain diagnostic measurements. The dataset used for this analysis is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective is to diagnostically predict whether a patient has diabetes using various medical predictor variables.
This project centers around a movie database containing comprehensive information about movies, including details such as titles, release dates, actors, genres, awards, and more.
The ALX Data Science Program is a rigorous, hands-on course that taught me strong data analysis and data science skills. I gained proficiency in Python, SQL, and machine learning techniques such as regression and classification. I also developed expertise in data visualization using Matplotlib and Seaborn, enabling me to turn complex datasets into actionable insights. I completed real-world projects on data wrangling, cleaning, and statistical analysis during the program. I applied data science methodologies to solve business problems and provide data-driven insights, enhancing my ability to analyze large datasets and present findings.
Completed a 5-month intensive program covering key data science tools and concepts including Python fundamentals, NumPy, Pandas, Matplotlib, Power BI, and machine learning basics. The program emphasized hands-on learning, version control (Git/GitHub), and real-world projects to build digital and analytical skills relevant to the job market. Developed a strong foundation in data analysis and applied these skills in community and academic contexts.
Currently mastering audience-centric Power BI visualizations for clear and relevant insights. Developing skills in emotional connection through ongoing exploration of concise dashboard elements like bar charts and small multiples. Actively exploring and implementing cognitive load reduction techniques in Power BI for enhanced data communication.
Introduction to Python Programming. Introduction to Data Analysis using Anaconda and Python data analysis packages. Data Wrangling, Clean data using Python and Pandas, and data visualization using Python.
Ask questions and answer them using data. Calculate key business metrics in financial analysis and interpret the values. Forecast financial metrics using scenario analysis, Digital Freelancing and the used platforms "globally and in the Arab world", and build an identity to work as a freelancer.
Intro to Research Methods. Create and interpret histograms, bar charts, and frequency plots. Central Tendency, Variability, Standardizing, Normal Distribution, Sampling Distributions.