As a Data Analyst at Curate Analytics, I collect, clean, and prepare large datasets to ensure accuracy and consistency. I conduct exploratory data analysis (EDA), apply statistical methods, and leverage machine learning techniques to uncover patterns and generate actionable insights. Using tools like SQL, Python, R, Tableau, and Power BI, I create compelling visualizations and automate reporting to support data-driven decision-making. I collaborate closely with stakeholders to translate complex data into strategic recommendations that align with business objectives and enhance client-centered solutions. Additionally, I stay updated on industry trends, continuously improving data processes and leveraging innovative approaches to drive business growth.

In my role at Curate Analytics, I worked on several projects that involved SQL to handle large datasets and derive actionable insights. One such project involved developing a comprehensive sales analytics platform for a retail client. The project started with extracting data from multiple sources, including transactional databases and inventory systems. Using SQL queries, I performed data cleaning, joining, and aggregation to create a unified dataset for analysis. I built complex queries to identify trends in sales performance across different regions, product categories, and time periods.

Additionally, I worked on a customer segmentation project that involved analyzing transactional data to group customers based on purchasing behaviour. I used SQL to filter and manipulate customer data, creating segments based on factors like purchase frequency, recency, and monetary value. This segmentation allowed the marketing team to target specific customer groups with personalized campaigns.

Both projects helped me enhance my SQL skills, particularly in writing efficient queries, optimizing performance, and using advanced SQL functions like window functions, subqueries and joins to derive insights from large, complex datasets. These experiences have strengthened my ability to transform raw data into valuable insights for business decision-making.

I successfully led a market expansion project for Unlimited Legacy (UXL) and Corrupted Denim, positioning both brands for growth in the competitive e-commerce space. Through extensive research on Amazon’s fashion and streetwear market, I identified key customer preferences, competitor strategies, and pricing trends, allowing for data-driven decision-making. By analyzing social media engagement, website traffic, and existing sales data, I uncovered valuable insights into customer behavior and purchasing patterns. I also conducted a thorough competitor analysis, benchmarking top-performing brands to refine pricing strategies, product descriptions, and marketing approaches. Leveraging my expertise in SEO, I optimized product listings to enhance visibility and drive sales. Additionally, I spearheaded targeted advertising campaigns, utilizing Google Analytics and Amazon Seller Central to track engagement and maximize reach. The culmination of this project was a comprehensive market research report, detailing strategic recommendations for product positioning, pricing optimization, and promotional strategies. This experience has strengthened my ability to conduct in-depth market analysis, develop actionable insights, and implement growth strategies, showcasing my expertise in driving brand success in the digital marketplace.These skills i implemented in scaling the brand from its humble beginnings in lagos nigeria to toronto canada can undeniably be an asset to this project and i would be estatic if given the opportunity