Opeyemi (Ismail) Peter

I am a Data Analyst with a strong interest in using data to solve business problems, identify trends, and support better decision-making. I have developed practical experience across SQL, Python, Excel, and Tableau, with a focus on data cleaning, validation, exploratory analysis, KPI development, and data visualization.

My analytical journey has involved building end-to-end projects using real-world datasets. One of my key projects was an Olist E-commerce SQL Analysis, where I worked with customer, order, payment, product, seller, and delivery data to investigate revenue, purchasing behaviour, product performance, seller performance, and delivery trends. I used SQL to transform the raw data into meaningful business insights and recommendations.

I have also completed a Nigeria Commercial Banking Experience Analysis, where I collected and analyzed information on commercial banks, including app ratings, customer reviews, digital banking features, USSD services, ATM availability, and other customer experience metrics. I used Excel for data validation and analysis and developed a dashboard to compare banking experiences across different institutions. I also used AI only as an additional validation step to cross-check parts of my data validation process and improve confidence in the accuracy of my work.

Another project I completed involved analyzing job market data to identify the most in-demand data roles, top hiring companies, locations with the highest number of opportunities, and platforms with the most job postings. I used Python for data cleaning and exploratory analysis and Tableau for visualization and dashboard development.

My primary interest is in business and data analytics, particularly understanding how data can be transformed into actionable information. I enjoy working with messy datasets, finding patterns that are not immediately obvious, defining meaningful KPIs, and presenting insights in a way that non-technical stakeholders can easily understand.

I am particularly interested in opportunities involving business intelligence, product analytics, commercial analytics, customer analytics, and operational analytics. I am also interested in continuing to strengthen my SQL, data modelling, reporting, and business analysis skills while working on real-world problems.

I consider myself curious, detail-oriented, and committed to producing accurate and well-supported analysis. I enjoy learning new tools and approaches, but I also believe that strong analytical work starts with understanding the business problem rather than simply using technology. My goal is to build a career where I can combine technical data skills with business understanding to help organisations make smarter, evidence-based decisions.