I'm Abdallah Alameer Ali
I am a Data and Business Intelligence Analyst with a strong foundation in data analytics and visualization. Holding a Bachelor's degree in Information Systems, I bring practical experience in building end-to-end data pipelines, cloud data warehouses, and comprehensive BI solutions. My technical expertise spans Advanced SQL, Python (including Scikit-learn for predictive analytics), Snowflake, Power BI, and Tableau to transform complex datasets into actionable, data-driven business insights.
Served as a Data Analyst Intern at CorporateStack, validating cross-functional enterprise operations and optimizing workflows across core ERP modules.
2026Earned the Associate Data Engineer in Snowflake certification from DataCamp.
2026Graduated with a Bachelor of Computer and Information Sciences, Information Systems from Ain Shams University.
2026Earned the Associate Data Analyst in SQL certification from Datacamp.
2026Served as a Data Analyst Intern at CodeAlpha, executing end-to-end data pipelines and applying NLP for sentiment analysis.
2026Completed the 120-hour Business Intelligence Development Trainee program at ITI.
2025Exploratory Data Analysis & Statistics
Proficient in deep data exploration, handling missing values, identifying outliers, and conducting statistical experiments to drive strategic business planning.
Business Intelligence & Visualization
Designing interactive dashboards and tracking core KPIs. Skilled in translating complex data into operational insights and dynamic reports for stakeholders.
Data Engineering & Predictive Analytics
Building end-to-end automated pipelines and leveraging machine learning models to forecast trends, predict behaviors, and uncover hidden business drivers.
Cloud Warehousing & Database Architecture
Engineering structured analytical schemas and managing large-scale datasets. Expertise in writing advanced queries to extract, transform, and load enterprise data.
AI-Powered HR Analysis Platform
Predictive Modeling: Developed an end-to-end Python platform using Scikit-learn, deploying a Random Forest Regressor for performance forecasting and a Gradient Boosting Classifier (with SMOTE) to predict promotion readiness. o Explainable AI (XAI) & Diagnostics: Implemented SHAP values with Logistic Regression to uncover core behavioral drivers of employee attrition, and applied Linear Regression to detect pay equity disparities. o Prescriptive Analytics: Built an automated recommendation engine that translates complex predictive outputs into actionable HR policies, enabling data-driven retention and talent development strategies.
SaaS Customer Churn & Retention Analytics
This project demonstrates the engineering of a Snowflake cloud data warehouse to analyze SaaS customer behavior. The goal was to process 280K+ records into a structured analytical schema and extract retention metrics, LTV, and churn drivers using advanced SQL.
PrimeRoute Logistics: Performance Dashboard
Developed a Power BI dashboard to transform complex logistics data into operational insights, designing an optimized Star Schema and authoring complex DAX for performance correlations.
Quantium Retail Analytics & A/B Testing
Conducted an end-to-end customer behavior analysis and A/B testing using Python (Pandas, SciPy). Developed a custom algorithm for control store selection combining Pearson Correlation and Magnitude Distance. Translated complex statistical findings into actionable C-level commercial recommendations to optimize shelf space and promotional strategies.
Insurance Risk & Claims Analysis Dashboard
he objective was to build a Power BI dashboard that provides: Clear KPI tracking Risk segmentation Demographic and behavioral analysis Interactive dynamic reporting 📊 KPI Metrics The dashboard includes the following key performance indicators: Total Policies – Measures the size of the customer base Total Claim Amount – Overall financial exposure Claim Frequency – Indicates how often claims occur Average Claim Amount – Measures claim severity Gender-wise Policy Distribution – Customer segmentation
📊 Business & Risk Analysis Dashboard
The goal to answer: Where is the revenue coming from How efficient is the cash collection? Where are the financial risks
Swiggy SQL Data Warehouse & Business Analysis
This project demonstrates the design and implementation of a SQL-based Data Warehouse using Swiggy order data. The goal was to transform raw transactional data into a structured Star Schema and extract business insights using analytical SQL queries.