AKUNIYA AGWANDAS
Data Analyst | IT Specialist | Developer
Data Analyst | IT Specialist | Developer
I'm a dedicated data analyst with expertise in turning complex data into actionable insights. With a background in Computer Engineering, I specialize in data visualization, statistical analysis, and developing machine learning models to solve real-world problems.
Alongside data anaysis, i have experience in other fields such as Networking, software development and so on.
My passions lies in Internet of Things, innovative and upcoming technology, and I'm constantly expanding my skillset to stay at the forefront of data analysis techniques and overall technology advancements.
Analyzed sales data from a retail company to identify trends and provide actionable insights that led to a 15% increase in quarterly revenue.
Developed a machine learning model that predicts electrical faults with 87% accuracy, helping technicians at power stations identify faults and implement proactive maintenance.
Monitoring system for electrical systems to access data and parameters online.
This dashboard visualizing electrical parameters across different substations, allowing users to explore trends and compare statistics.
This is a security system that alerts via phone notification and Email when a gas or water leak is detected
It implements IoT using sensors that trigger the alerts and safety lights when gas and moisture levels rise above threshold
This project involved analyzing sales data from a major retail company to identify trends, patterns, and areas for improvement. Using Python for data processing and Tableau for visualization, I delivered actionable insights that led to a 15% increase in quarterly revenue.
The retail company had 3 years of sales data across multiple stores nationwide but struggled to understand seasonal trends, product performance, and customer demographics. They needed clear visualizations and recommendations to optimize their inventory and marketing strategies.
I developed a comprehensive analysis pipeline that included:
For this project, I developed a machine learning model to predict electrical faults for power stations. The model achieved 87% accuracy in identifying potential faults, allowing for proactive maintenance and reducing downtime.
Power stations were experiencing unexpected equipment failures leading to costly downtime and repair expenses. The challenge was to develop a predictive system that could analyze sensor data and identify potential failures before they occurred.
I built a comprehensive fault prediction system that included:
This project involved creating a smart monitoring system for electrical grids that enables online access to real-time data and parameters. This system allows remote monitoring of critical electrical infrastructure and facilitates timely interventions.
Traditional electrical monitoring systems required physical presence at substations for readings and diagnostics. The goal was to create a system that allowed remote access and real-time monitoring of critical parameters to improve maintenance efficiency and reduce response times.
I developed an IoT-based smart monitoring system with the following components:
This project involved creating an interactive dashboard to visualize electrical parameters across different substations. The dashboard allows users to explore trends, compare statistics, and understand the performance of the electrical system.
There was a large amount of electrical data being collected, but limited tools for non-technical users to easily visualize and understand the information. The goal was to create an accessible, user-friendly dashboard for visualization and analysis.
I developed an interactive dashboard using Python's Dash framework and Grafana with the following components: