Automated Personal Spending Dashboard

Description

This project demonstrates how to collect, store, transform, and visualize personal spending data. 

The system collects data through Google Forms, stores it in Google Sheets, loads into BigQuery and finally visualizes everything in Looker Studio using dynamic charts and KPIs. 

The goal was to eliminate manual data entry and achieve a real-time, always-updated personal finance dashboard. 

A brief summary of the key metrics from the project

This project analyzes the performance of image and video ad campaign over 60-day period to identify which format drives stronger engagement and conversions. 

 Key Metrics

  * Savings Rate: 20.47%

  * Total Income: ₦9,755,000

  * Total Expenses:₦7,758,500

  * Net Balance:₦1,996,500

  * Current vs Previous Month Expenses:

     - ₦410,000: 26.1% from previous month

  2. Spending by Category

  * Income greatly outweighs other categories

  * Highest expense categories:

     - Operating Expenses

     - Investments

     - Capital Expenditure

     - Discretionary spending is the lowest

  3. Spending Over Time

  * Spending peaked in January 2025 (house rent + yearly obligations)

  * Another peak occured in October 2025

  4. Spendnig by Description

  * Groceries & Food recorded the highest amount

  * Followed by House rent, and emergency fund deposit

Collaboration & Outcome of the Project

I executed thi sproject independently, managing the full analytics workflow; from designing the automated data collection pipeline to building the real-time spending dashboard. I handled the setup of Google Forms, Google Sheets automation, ETL  logic, data cleaning, transformation, and dashboard development in Looker Studio. Even though it was a solo project, i approached it with a collaborative mindset by applying industry-standard practices and documentation to ensure the workflow can be easily understood or extended by other analysts