Hello I’m Usama Tahir

Power BI Sales Report

The Car Sales and Orders Dashboard is an interactive data visualization tool designed to provide in-depth insights into car sales performance. By analyzing sales and order data from 2003 to 2005, the dashboard allows users to track yearly sales trends, compare monthly and quarterly performance, and analyze key metrics such as total sales, top-selling models, and regional sales distribution.

Built using Power BI, it features dynamic visuals, interactive filters, and customizable views that make it easy to explore the data at various aggregation levels.

The dashboard is an invaluable resource for understanding sales patterns, identifying growth opportunities, and making data-driven business decisions

AquaMetrics

Aqua Metrics (Wastewater Management KPI Analysis) is a data-driven project designed to optimize the performance of wastewater treatment plants by analyzing key performance indicators (KPIs). Using Python in a Jupyter Notebook environment, the project explores various metrics to provide actionable insights into the operation and efficiency of these facilities. By examining data from multiple treatment plants, AquaMetrics identifies trends and performance gaps, enabling better resource allocation and improved operational efficiency.

The project focuses on several critical KPIs, including the volume of wastewater handled by each plant, the utilization rates, and the efficiency of treating wastewater to quality standards. Through visualizations such as bar charts, pie charts, and line graphs,

AquaMetrics uncovers valuable insights, such as identifying the most and least utilized plants, understanding the contribution of wastewater from different sources, and analyzing day-wise activity trends. These analyses help stakeholders make data-backed decisions to enhance plant performance and meet environmental compliance goals.

Thermal-Aware Data Center Workload Simulator

Managing the temperature in data centers is a critical challenge due to the continuous operation of servers, which generate significant heat. High temperatures can adversely affect essential components such as server racks, power supplies, and cabling systems. Traditional cooling systems are expensive and energy-intensive, prompting the need for more efficient solutions. To address this, I developed thermal-aware load balancing policies that intelligently manage workloads to minimize heat generation by servers.

These policies monitor the heat generated by each server and optimize workload distribution to keep data center temperatures under control. By reducing heat output, the reliance on costly cooling systems is minimized, resulting in significant cost savings and improved energy efficiency. This approach also ensures the smooth operation of data center components by maintaining stable thermal conditions.

To support this solution, I implemented a visualization tool that provides real-time insights into the heat generated by servers. This allows administrators to make informed decisions about load balancing strategies tailored to their data center's specific needs. The project not only improves operational efficiency but also promotes sustainable practices in data center management, aligning with modern goals for energy conservation and cost-effectiveness.

ETL Pipeline

This project highlights the creation of a robust end-to-end data pipeline to process real estate data from Redfin, utilizing modern data engineering tools and practices. The pipeline begins with data extraction, followed by storing raw data in an AWS S3 bucket. The data is then cleaned and transformed to ensure it is analysis-ready, with the transformed version stored in a separate S3 bucket. This systematic approach ensures efficient data processing and storage at each stage.

The pipeline leverages Snowflake for scalable and efficient data warehousing, with Snowpipe automating the ingestion of transformed data. Once in Snowflake, the data is connected to Power BI, where insightful visualizations are created to explore trends and derive meaningful insights. This project demonstrates expertise in data extraction, transformation, storage, and visualization, showcasing the integration of cloud services, ETL processes, and business intelligence tools.