Vincent Momanyi – Data Projects Portfolio

After Completion of the Four projects ie:

-Sales Performance Dashboard Using Excel

-SQL-Based Analysis of Product Sales

-Web Scraping and Analysis of Job Postings

-Power BI Dashboard for Retail Insights

---

Projects Overview

1. Sales Dashboard Project – Excel

Purpose: Create an interactive Excel dashboard for analyzing sales and revenue data.
Key Features:

• Pivot tables by product, region, and category
• Revenue trends by month and year
• Dynamic slicers and charts (line, bar, filled maps)
• KPI analytics: Total Revenue, Total Orders, Top Products & Customers
  Technologies: Excel, Pivot Tables, Formulas, Conditional Formatting
  File: SalesDashboard.xlsx
  Usage: Filter by region, product, or time period; refresh pivot tables for updated data.

---

2. Power BI Dashboards

Purpose: Develop interactive Power BI dashboards to visualize sales trends and regional performance.
Key Features:

• Filled maps for geographic insights
• Top revenue by category and region
• Dynamic slicers affecting multiple pages
• Time-based trend analysis (monthly/yearly revenue)
  Technologies: Power BI Desktop, DAX, Data Modeling, Slicers

---

3. Python Data Analysis Projects

Examples:

• Skills Matrix Analysis: Cross-tab analysis of employee skills, handling empty values and duplicates.
• MySQL + Python Integration: Automated queries and data retrieval for product sales.

Technologies: Python, Pandas, NumPy, Matplotlib, SQL

---

4. Data Cleaning & Preprocessing Utilities

Purpose: Ensure raw data is clean, structured, and ready for analysis.
Key Features:

• Removing duplicates and formatting data
• Handling repeated orders and missing values
• Calculating totals, averages, and unique counts efficiently

---

5. KPI & Revenue Tracking

Purpose: Monitor key business metrics across projects.
Tracked Metrics:

• Total Revenue & Orders
• Top Products & Customers
• Regional revenue performance
• Monthly and yearly trends

Tools Used: Excel, Python, Power BI

---

Common Technologies Across Projects

• Microsoft Excel: Pivot tables, formulas, dashboards, filled maps
• Python: Pandas, NumPy, Matplotlib
• SQL: MySQL integration and data extraction
• Power BI: Interactive dashboards, DAX, slicers, visual analytics

---

Future Improvements

• Automate data imports from CSV, SQL, and APIs
• Integrate dashboards with Power BI for enhanced visuals
• Implement dynamic forecasting models
• Generate automated monthly reports directly from dashboards

---