Olajide Abdullateef

Data Engineer | Data Analyst

Projects

NBA Playoff Outcome Prediction Pipeline

This project analyzes NBA team and player statistics from the 2022–2023 and 2023–2024 seasons to generate predictive insights for the 2024–2025 NBA playoffs using comparative and statistical analysis. Leveraging Snowflake, DBT and PowerBi, the result is a scalable analytics workflow supporting predictive insights and data visualization.

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Unlocking Business Insights: The Analytics Hackathon 2025

This project presents an in-depth analysis, revealing key insights into sales performance, customer behavior, product trends, and regional business drivers for a global manufacturing company. Leveraging SQL, data modeling, and visualization techniques, I examined four years of transactional data to identify high-value insights backed by evidence and clear business reasoning. The analysis highlights revenue patterns, product demand and customer engagement, providing data-driven recommendations to enhance sales efficiency, inventory management, and strategic decision-making.

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Data Community Africa (DCA) Hackaton 2025

Designed and implemented a comprehensive data pipeline for analytics, leveraging Airflow, s3, AWS Redshift and DBT. The pipeline automates data ingestion from S3 to Redshift, transforms datasets with dbt and enables the creation of interactive dashboards. Specifically, it supports a streamlit dashboard for real-time monitoring of patients, diseases, and inventory, as well as a PowerBI dashboard for data-driven insights and decision making.

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Native SQL Data Pipeline : Incremental Processing in Cloud Data Warehouse

Designed and implemented a fully incremental data pipeline using native SQL (functions and triggers) within a cloud data warehouse, eliminating the need for external tools. The pipeline features a multi-layered architecture (Raw → Silver → Gold → Dashboard) optimized for efficient monthly data processing and analysis.

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Holiday Sales Impact Analysis: Uncovering Patterns in consumer Demand

This project examines the impact of four major holidays—Christmas, Super Bowl, Labor Day, and Thanksgiving—on sales performance, aiming to uncover unique patterns in consumer demand. By analyzing sales data, the project provides actionable insights to inform inventory planning, marketing strategies, and business decision-making, helping businesses capitalize on holiday-driven opportunities.

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