Hamza Mueen

• Sales Data Automation & ETL: Took full ownership of the automation process, enhancing the existing workflows for sales data collection and ETL using Python, SQL, and Apache Airflow. Introduced optimizations that improved efficiency in processing data from multiple databases and e-commerce platforms.
• New Product Launch Analysis: Led the effort in refining web scraping techniques with tools like BeautifulSoup and Pandas, integrating product data from new retailers and maintaining a scalable and accurate data pipeline for product launch analysis.
• Inventory Management & Demand Forecasting: Developed and maintained advanced predictive models in Python, integrating real-time stock data to improve accuracy in forecasting demand and optimizing stock levels.
• Data Visualization & Dashboards: Designed and managed comprehensive, interactive dashboards using Power BI, Tableau, and Apache Superset, providing real-time insights into sales trends, store performance, and product metrics, helping leadership make informed business decisions.
• Dashboard Development & Reporting: Built and maintained advanced, scalable sales dashboards in SQL, providing stakeholders with critical KPIs and sales metrics in real time. Implemented new features to improve data accessibility and user experience.

Sales Data Automation & ETL: Collaborated with the team to automate monthly sales data collection using Python, SQL, and Apache Airflow. Assisted in implementing ETL processes to extract data from e-commerce platforms and databases, transforming and loading it into storage solutions.

• New Product Launch Analysis: Leveraged web scraping tools like BeautifulSoup and Pandas to collect and integrate product data from retailers, ensuring consistency and accuracy in the database for analysis.
• Inventory Management & Demand Forecasting: Supported the development of data pipelines for inventory tracking, using predictive modeling techniques to help forecast demand based on historical data.
• Data Visualization & Dashboards: Created basic interactive dashboards in Power BI and Tableau to help business users monitor key metrics, such as sales trends and product performance.
• Dashboard Development & Reporting: Contributed to building responsive sales dashboards using SQL to present key performance indicators (KPIs), enabling data-driven decision-making for stakeholders.

Competitor Analysis (FYP)

• Project Overview: Developed an online platform that offers competitive analysis of various industries to entrepreneurs, established businesses, and consumers. The platform provides interactive dashboards, enabling users to gain insights into market trends and competitors' strategies.
• Data Collection & Processing:Leveraged web scraping techniques to gather data from multiple industry websites. The data was processed and stored in a relational database, ensuring efficient retrieval and analysis.
• Dashboard Development: Utilized Apache Superset to design and deploy interactive dashboards. These dashboards provide users with real-time data visualization and customizable analytics, enhancing decision-making processes.
• Technologies Used: Python, BeautifulSoup, SQL, Apache Superset, HTML/CSS, WSL (Windows Subsystem for Linux).
• Outcome: Successfully created a monetizable platform that offers valuable competitive insights, contributing to data-driven business decisions for clients across various industries