Data Analyst

Hello, I'm
Dalia Akram.

I turn raw data into clear, meaningful stories — using Python, SQL, and visualization to reveal what numbers quietly say.

View My Work Download CV
3+
Completed Projects
3
Languages Spoken
5+
Tools & Libraries

About Me

Curious mind.
Data-driven approach.

I'm a Junior Data Analyst with hands-on experience in Python, SQL, and data visualization — completing projects that span exploratory analysis, data cleaning, and building automated pipelines.

What draws me to data analysis is the detective work: finding patterns hidden in messy datasets, asking the right questions, and communicating the answers so anyone can understand them.

I'm trilingual — fluent in Arabic, Russian, and English — which shapes how I approach problems: with multiple perspectives, precision in communication, and genuine curiosity.

Languages

🇸🇦 Arabic — Native 🇷🇺 Russian — Professional 🇬🇧 English — B2

Soft Skills

  • Problem-Solving & Critical Thinking
  • Data Communication & Storytelling
  • Research & Documentation

Selected Projects

What I've built
so far.

Exploratory Data Analysis

Nobel Prize
Data Analysis

An in-depth exploration of Nobel Prize history, focusing on gender representation, category distribution, and how female participation has evolved from 1901 to present day. Uncovering the story behind who gets recognized — and who doesn't.

Python Pandas Matplotlib Seaborn Kaggle Dataset
  • Female participation has increased steadily since the 1970s
  • Literature & Peace were earliest categories with female laureates
  • Visualized long gender gaps across scientific fields
  • Tracked decade-by-decade shifts in category dominance
↗ GitHub Repo View Notebook
★

Gender participation over decades

Exploratory Data Analysis

Online Learning
Engagement & Dropout Risk

An analysis of student behavior patterns on online learning platforms, identifying which engagement factors — login frequency, device type, course category — are most predictive of dropout risk. Turning behavioral signals into actionable insights for learner success.

Python Pandas Matplotlib Seaborn Kaggle Dataset Power BI
  • Investigated whether engagement frequency reduces dropout risk
  • Compared dropout rates across device types (mobile vs desktop)
  • Identified which course categories had highest risk scores
  • Ranked engagement metrics by dropout correlation strength
  • Built an interactive Power BI dashboard to visualize dropout risk patterns
↗ GitHub Repo View Notebook
73%

engaged learners

engagement patterns by student

SQL Analysis

Olist Brazilian E-commerce
Data Analysis

Analysis of the Olist Brazilian E-commerce dataset using MySQL. Covers data loading, schema design, and business insights through SQL queries.

MySQL DDL/Schema Design Joins Window Functions Aggregate Functions
  • Calculated total platform revenue and monthly order trends to identify peak trading periods
  • Measured late delivery rate and order status distribution to surface fulfilment performance
  • Ranked top product categories and cities by order volume using RANK() window function
  • Identified states with revenue above average using a correlated subquery
↗ GitHub Repo
TOTAL REVENUE R$16M+ ORDERS 99K+ LATE DELIVERY ~8% MYSQL · 5 TABLES · WINDOW FUNCTIONS

Skills & Tools

What I work with.

Programming

Python (Pandas, NumPy) Intermediate
SQL (Queries, JOINs) Intermediate

Visualization

Matplotlib Intermediate
Seaborn Intermediate
Power BI Basic

Spreadsheets

Microsoft Excel Intermediate
Google Sheets Intermediate

Core Competencies

Exploratory Data Analysis
Data Cleaning & Preprocessing
Statistical Analysis

Platforms & Tools

GitHub Version Control
Kaggle Datasets
Jupyter / Google Colab Notebooks

Let's Connect

Open to opportunities.
Let's talk data.

I'm actively looking for junior data analyst roles, internships, or collaborative projects. If you have something in mind, I'd love to hear from you.

✉ Email Me GitHub LinkedIn Kaggle

© 2026 Dalia Akram · Built with curiosity