FINANCIAL ANALYSIS PROJECT

PROJECT DESCRIPTION

This project delivers clear, actionable insights into business financial performance by deeply analyzing revenue data across multiple business dimensions: - Product/Service Sub-Categories - Company Branches / Locations - Different Payment Methods

The final output is a clean, interactive Power BI dashboard that helps stakeholders quickly: - Identify the strongest revenue drivers - Discover monthly trends & seasonality - Compare branch performance - Understand payment method patterns - Make better strategic decisions (marketing • resource allocation • expansion • operations)

TECHNOLOGY & TOOLS USED

**Microsoft Excel** → Data preparation & understanding
**Power BI Desktop** → Data modeling • DAX • Visualization • Dashboard

KEY BUSINESS ANSWERED

- Which **product categories** generate the most revenue?
- Which **branches** are performing best / need attention?
- How do **revenue trends** look month-to-month?
- Which **payment methods** are most popular & valuable?
- Is the business showing **growth**, **seasonality**, or **warning signs**?

STEP-BY-STEP PROCESS

1. **Data Loading**  
   Import Excel file → `FINANCIAL ANALYSIS PROJECT.xlsx`
2. **Data Cleaning in Power Query**  
   - Remove duplicates  
   - Handle missing/empty values  
   - Fill missing values (when appropriate)
3. **Date Table Creation**  
   ```dax
   DATE TABLE = CALENDARAUTO()
4. Extract Helpful Date Columns  
   DAX
   Month Name = FORMAT('DATE TABLE'[Date], "MMMM")
   Day Name   = FORMAT('DATE TABLE'[Date], "DDDD")

ADD CALCULATED TABLE

* Step 5: Using the Date column from the dataset to create a date table
           . DATE TABLE = CALENDARAUTO()

* Step 6: Extracting the month and day from the Date Table
          - MONTH = FORMAT('DATE TABLE'[Date],"MMMM")
          - DAY = FORMAT('DATE TABLE'[Date],"DDDD")

KEY METRICS & DAX MEASURES

* Step 7: TOTAL TRANSACTION = COUNT(Sheet1[Transaction ID])

* Step 8: TOTAL AMOUNT = SUM(Sheet1[Amount])

* Step 9: AVERAGE REVENUE = AVERAGE(Sheet1[Amount])

* Step 10: TOTAL REVENUE = CALCULATE(COUNT(Sheet1[Revenue or Expense]),'Sheet1'[Revenue or Expense]="REVENUE")

* Step 11: TOTAL EXPENSE = CALCULATE(COUNT(Sheet1[Revenue or Expense]),'Sheet1'[Revenue or Expense]="EXPENSE")

VISUALIZATIONS

* Step 12: Revenue by sub-category <Stacked Bar Chart>
            This chart describes how revenue is broken down by sub-categories in the dataset. It helps to identify key revenue drivers, access
            performance trends and support strategic financial decisions.

* Step 13: Correlation between Payment Method <Donut Chart>
            It explores how payment methods(e.g card, mobile phone, transfer, cash) correlate with financial metrics like revenue, transaction
            volume in the dataset aiding in optimizing payment strategies and financial planning. 

* Step 14: Revenue trends by month <Line Chart>
            This chart explains how to analyze monthly revenue trends to identify seasonality, growth patterns and anomalies. It helps stakeholders
            plan budgets, forecast performance and optimize strategies for product/service segment.

* Step 15: Branch vs sub-category <Matrix>
            It clarifies the difference between branch and sub-category and how they are used to analyze revenue, comparing these dimensions helps
            identify which location or product drive revenue.

* Step 16: Revenue by sub-category <Tree Map>
            This explains how revenue is distributed across subcategories (are specific product or service segments). This analysis helps identify
            key revenue drivers and inform strategic financial decisions.

* Step 17: Revenue by branch <Stacked Bar Chart>
            This chart explains how revenue is distributed across branches. It helps to identify high-performing locations and supports decisions 
            on staffing, operations or regional strategies.

ADD INTERACTIVITY WITH SLICERS

1. Select the slicer visual: In the visualizations pane (on the right), click the slicer icon. This adds a blank slicer to your report canvas.
2. Add a field to the slicer: In the fields pane, locate the dataset and drag the field you want to filter (Year and Branch) into the 
   or values area of the slicer.
3. Resize and format the slicers to control user interactions.

CONCLUSION

This dashboard visualizes key financial metrics focusing on monthly revenue trends,profitability, identifying high-performing locations
and key revenue drivers. Built for analyst and investors, it supports strategic decision-making by highlighting growth patterns and risks.
The visualizations and underlying data are accessible via the dashboard.