💰 Personal Finance Dashboard - Power BI

A Microsoft Power BI project that analyzes personal financial data and visualizes expenses through an interactive dashboard.

##🗣 "Data analysis is not just about presenting data, but to build a story and create a meaningful narrative from the raw data. At the end of the day, that's what analytics is all about - not about writing code, not about crunching ## ## numbers, not about memorizing formula syntax - it's about deriving meaning and context from the data and, more importantly, using it to make real change."

- Chris Dutton, Maven Analytics

🎯 Problem Statement

I have been tracking my daily expenses using Microsoft Excel. While sorting/filtering in Excel gives a basic overview, a deeper financial analysis requires an interactive dashboard.

🔍 This project transforms static Excel data into dynamic Power BI dashboards, providing detailed insights into spending habits.

📌 Project Goals

The Power BI dashboard aims to answer:

✔️ Monthly spending trends (for a given year)

✔️ Total spending per item category

✔️ Detailed expense list with comments

✔️ Spending distribution by location

✔️ Number of purchases in different price ranges

✔️ Quarterly and weekly spending insights

✔️ Average spending per week, month, day

✔️ Food vs. restaurant spending comparison

✔️ Spending behavior when I am sick

✔️ Comparison of weekday vs. weekend spending

📊 Data Analysis Summary

📌 Below are screenshots of the Power BI dashboards:

1️⃣ Executive Summary Dashboard

2️⃣ Granular Financial Insights Dashboard

🛠 Hardware & Software Used

Microsoft Power BI Desktop (v2.93) Microsoft Excel (for raw financial data) Python (v3.8) (for pre-processing) Python Libraries: openpyxl, os Windows 10 Machine Apple iPad (7th Gen) + Pencil (for handwritten annotations)

📌 Overview of Microsoft Power BI

Microsoft Power BI is a business intelligence (BI) tool for loading, modeling, and visualizing data. It was first released in July 2011 and has since evolved into a powerful data visualization platform.

Power BI offers two modes:

✔️ Power BI Desktop (for local analysis)

✔️ Power BI Service (for cloud-based dashboards & collaboration)

Power BI enhances data storytelling through interactive visualizations called dashboards.

📂 Project Files & Structure

File/Folder Description Finance_Data/20xx/ Folder containing monthly Excel expense data (Aug 2018 - Dec 2020). change_excel_sheets.py Python script to rename all Excel sheets to "Sheet1" (Power BI requirement). Finance_Data.xlsx The original Excel file tracking daily expenses. Personal_Finance_Dashboard.pbix Power BI Dashboard file with financial visualizations.

📊 Data Collection & Cleaning

📥 Data Collection

I manually recorded my expenses by keeping purchase receipts and inputting details into Excel, including: Date Item Category Price Purchase Location Additional Comments

🧹 Data Cleaning & Preprocessing

✔️ Standardized categories (e.g., merging "Hair-Cut", "hair cut" → "Hair Cut")

✔️ Formatted date columns (converted text-based dates to correct format)

✔️ Handled missing values (few rows were removed)

✔️ Reformatted Excel sheets for Power BI compatibility

📊 Measure Creation & Visualizations

To generate meaningful insights, I created lookup tables and DAX measures in Power BI:

📌 Lookup Tables Created:

1️⃣ Calendar Lookup – Created month, quarter, and week-based time analysis.

2️⃣ Item Lookup – Added a manual filter to include/exclude rent payments.

3️⃣ Location Lookup – Consolidated distinct purchase locations.

📌 DAX Measures Created:

✔️ Total Cost Calculation

✔️ Spending Trends by Week, Month, Year

✔️ Price Ranges for Purchases

✔️ Average Cost Per Day & Week

✔️ Boolean Filter for Sick Days Analysis

📌 Visual Elements Used:

Slicers for granular filtering (by year, month, day, category). Comparison Visuals for food vs. restaurant expenses. Interactive Charts to analyze spending habits over time.

🚀 How to View My Power BI Dashboard

🖥️ Step 1: Install Power BI Desktop

🔗 Download Power BI for Free

⚙️ Step 2: Configure Power BI Settings

Open Power BI Desktop Go to: File → Options and settings → Options Under Global Settings, disable all Preview Features Under Current File → Data Load, deactivate auto-detect relationships

📥 Step 3: Download Project Files

Clone this GitHub repository git clone https://github.com/your-username/personal-finance-powerbi.git cd personal-finance-powerbi Open Personal_Finance_Dashboard.pbix in Power BI Explore & analyze the dashboards 🚀

🔮 Future Enhancements

💡 Ideas for future improvements:

✔️ Improve UI/UX with modern dashboard templates

✔️ Generalize the dashboard for wider public use

✔️ Add automated Excel data processing with Python

✔️ Create mobile/tablet-optimized views in Power BI

🙏 Acknowledgements

🚀 Microsoft Power BI Team – for creating a powerful BI tool.