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Welcome to my creative space.
I'm Abdulbasit Abdulhameed, a Data Analyst. I help businesses understand their performance and make better decisions with their data by turning their sales and financial data into clear reports and dashboards.
If you run a business and struggle to keep track of your numbers, I build systems that help you record and understand your performance so you can make better decisions.
I also help businesses present themselves better through design, such as
This is where I share my work and what I've learned along the way. Glad to have you here.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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PROFESSIONAL SUMMARY
Data-driven professional with strong expertise in Data Analysis, Excel, and SQL. Proficient in building data dashboards, performing complex data cleaning, and deriving actionable business insights. Demonstrated ability to work with large datasets (1400+ records) and create comprehensive analytics solutions. Seeking part-time opportunities to leverage analytical skills while expanding expertise in data-driven decision-making.
TECHNICAL SKILLS
Data Analysis & Visualization: Excel (Advanced), SQL (Intermediate), Data Cleaning, Data Modeling
Excel Expertise: Advanced formulas, VLOOKUP, Pivot Tables, Dashboards, Data Validation, Conditional Formatting
SQL Skills: Query writing, Data extraction, Database analysis
Programming: Python (Basic).
Project Links :
I analyzed 3M+ job postings across 161 countries and 93K companies to identify hiring trends, in-demand roles, work-mode patterns, and salary insights.
I used Python for data cleaning and preprocessing, SQL for analysis, and Power BI to build an interactive dashboard.
Key areas analyzed:
• Global hiring demand
• Top job roles by demand
• Remote vs. onsite/hybrid work patterns
• Average salary trends
• Monthly hiring trends
This project helped me turn a large dataset into clear, actionable insights for understanding the global job market.
Retail Sales Data Analysis — SQL
A SQL-based data analysis project focused on exploring retail sales data and extracting meaningful business insights from transactional records.
Key areas covered:
• Data exploration and preparation
• Sales and revenue analysis
• Product and category performance
• Customer and transaction analysis
• Aggregation using GROUP BY and HAVING
• Filtering and conditional analysis using WHERE and CASE WHEN
• JOINs and subqueries
• CTEs for structured analysis
• Window functions for ranking and comparative analysis
The project demonstrates how SQL can be used to transform transactional data into meaningful insights and answer practical business questions.
