Hi, I’m James Mwangi, a data analyst with a passion for turning raw data into meaningful insights. With expertise in data cleaning[SQL], visualization[Excel & Power Bi], and predictive analytics[R], I help businesses make data-driven decisions that drive growth.
I believe data is more than just numbers—it's a story waiting to be told.
Let’s uncover insights and drive impactful decisions together! 🚀
In this project we analyze walmart sales data to identify key performance indicators and uncover actionable insights.
The insights gained can then be used to optimize inventory management, improve marketing strategies, and enhance overall business performance.
A SQL and Power BI Project.
A SQL and Power BI Project.
This project aims to provide insights into employees age, race, gender, job title, location and the length of employment from 2000 to 2019.
By analyzing various aspects, we seek to uncover actionable insights, identify trends, gain a deeper understanding of the employee performance and make data-driven recommendations.
This project contains the resources for a financial sales analysis visualization project. We aim to provide interactive and insightful visualizations of financial data, enabling users to understand trends, patterns, and key performance indicators (KPIs) effectively.
We explore and clean the data with SQL,then visualize with Power BI.
In this project, we analyze call center data to identify trends, patterns and areas of improvement. We explore metrics such as call volume, average handling time, customer satisfaction scores, and call sentiment. The insights gained from this analysis will be used to make data-driven decisions, allocate resources effectively and implement process improvements.
An Excel Project.
A case study that involves data cleaning, exploratory data analysis (EDA), and advanced analytics on sales data. The objective is to extract insights, visualize trends, and perform forecasting.
An R Project.
This project focuses on analyzing employee salary data using SQL queries to answer key questions related to job titles, base pay, overtime pay, and total compensation.
A SQL Project.
This project involves data cleaning and exploratory data analysis (EDA) of a layoffs dataset. We use SQL queries to clean the data, identify missing values, and perform data validation. We then analyze the data to identify trends, patterns, and insights that can be used to make data-driven decisions.
A SQL Project.