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This Power BI dashboard provides a comprehensive overview of ATM transactions, costs, and revenues across different regions. It is designed to help stakeholders understand the performance, costs, and trends in ATM operations.

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ATM Transaction Dashboard

This Power BI dashboard provides a comprehensive overview of ATM transactions, costs, and revenues across different regions. It is designed to help stakeholders understand the performance, costs, and trends in ATM operations.

Dashboard Overview

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Cost Analysis (ATM Cost and Maintenance)

This section provides a breakdown of ATM maintenance costs, categorized and visualized using pie charts for the selected month (March). The categories include:

  • CRA: Cash Replenishment Agency
  • ATM AMC: ATM Annual Maintenance Contract
  • Site Maintenance: Maintenance of the ATM site
  • Spare Replacement: Replacement of ATM spare parts
  • UPS AMC: Uninterruptible Power Supply Annual Maintenance Contract
  • VSAT AMC: Very Small Aperture Terminal Annual Maintenance Contract

Key Metrics

  • Total Cost: 296M
  • Average Total Transactions (TXN): 178.89M
  • Gross Profit Percentage: 59.6%
  • Average Uptime: 91.9%
  • Average EBILL: 2.21K

Revenue Analysis (ATM, MHA, and Monthly Revenue)

This section highlights the revenue generated from ATMs, MHA (Ministry of Home Affairs), and overall monthly revenue across various regions. The regions analyzed include:

  • Assam
  • Punjab
  • Jammu & Kashmir
  • Manipur
  • Tripura
  • Nagaland
  • Meghalaya
  • Mizoram
  • Arunachal Pradesh
  • Ladakh
  • Sikkim

Financial Transactions (Fin Txn) and Non-Financial Transactions (Non-Fin Txn) by Month

This section compares the number of financial transactions to non-financial transactions across different months:

  • March
  • December
  • August
  • November

Transactions by Date

This line chart shows the trend of total transactions over time, specifically highlighting the months:

  • March 2024
  • May 2024
  • July 2024
  • September 2024
  • November 2024

How the Dashboard Was Created

Data Collection

Data was collected from various sources including ATM transaction logs, maintenance records, and financial reports. The data was cleaned and prepared for analysis using data preprocessing techniques.

Visualization

  • Power BI: The primary tool used for creating this dashboard.
  • Charts Used:
    • Pie Charts: For visualizing the cost breakdown in the Cost Analysis section.
    • Bar Charts: For comparing revenue across regions and transaction types by month.
    • Line Chart: For showing the trend in transactions over time.

Insights Derived

  • Cost Efficiency: By breaking down costs into specific categories, stakeholders can identify areas for cost-saving measures.
  • Revenue Streams: Understanding revenue contributions from different regions helps strategize regional focus and improve profitability.
  • Transaction Trends: Monitoring trends in financial and non-financial transactions aids in predicting future transaction volumes.
  • Performance Metrics: Key performance metrics like average uptime and gross profit percentage provide a quick snapshot of overall efficiency and profitability.

Importance of These Insights

  • Operational Efficiency: Identifying cost drivers and optimizing maintenance costs can enhance operational efficiency.
  • Strategic Planning: Revenue insights assist in making informed decisions about resource allocation and marketing strategies.
  • Predictive Maintenance: Trends in transaction data can support predictive maintenance of ATMs, ensuring higher uptime and better customer service.
  • Financial Performance: Key metrics help assess the financial health of the ATM network, guiding decisions to improve profitability.

About

This Power BI dashboard provides a comprehensive overview of ATM transactions, costs, and revenues across different regions. It is designed to help stakeholders understand the performance, costs, and trends in ATM operations.

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