Portfolio

Dashboards

Power BI Dashboards and Data Visualizations

Water-quality-analysis

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Water water_quality Dashboard Water water_quality Dashboard

Water_quality And Infrastructure_improved Dashboard

Water_quality And Infrastructure Dashboard Water_quality And Infrastructure Dashboard

Sales Analysis Dashboard

Revenue Analysis Dashboard Revenue Analysis Dashboard

Adventure Works Order Report Dashboard

Adventure Works Order Report Dashboard Adventure Works Order Report Dashboard

SQL Projects

Exploratory Data Analysis and Data Queries

  • Auditing on Maji Ndogo water project

    • This project was developed using SQL to clean and standardize inconsistent data, identify and correct inaccurate records, and prepare the dataset for reliable data modeling. The process involved data validation, outlier detection, handling missing values, and transforming raw data into a structured format suitable for in-depth analysis and decision-making.

  • Water Accessibility Insights with Complex Queries

    • This project involves advanced SQL queries to clustering data to unveil Maji Ndogo's water and This survey aimed to identify the water sources people use and determine both the total and average number of users for each source. Additionally, it examined the duration citizens typically spend in queues to access water crisis

  • Water access project reporting using advanced SQL Queries

    • This project utilizes advanced SQL techniques—including Common Table Expressions (CTEs), window functions, subqueries, and complex joins with aggregations—to analyze water access data. The goal is to uncover trends and patterns that help identify areas with clean water access, guide infrastructure installations, and support improvements to existing systems.

  • Auditing the Maji Ndogo water project Data Analysis

    • This project involves advanced SQL queries to analayze sales data, uncovering trends and patterns to optimize sales strategies, and improve forecassting accuracy

Python data analysis intership Projects

Exploratory Data Analysis

  • International Restaurants Data Analysis

    • Overview:- This analysis explores international restaurants across various countries and cities, focusing on key metrics such as cuisine types, ratings, pricing, popularity, and geographic distribution. The goal is to identify trends, high-performing markets, and potential opportunities for investment or expansion.

    🐍Programing languages and uselfull libraries i have used during EDA analysis

  • Python programming language
  • Scikit-learn

    • Scikit-learn is important for classic ML algorithms (regression, clustering, etc.)

  • Pandas and NumPy

    • Pandas are used for data manipulation and analysis using DataFrames and NumPy is used for numerical computing and array manipulation

  • Matplotlib and Seaborn

    • Matplotlib is a basic plotting ,charting and seaborn is for statistical data visualization (built on matplotlib)

  • plotly

    • plotly is for interactive and web-based visualizations