Client : A leader in global payment services, managing over 100,000 ATMs and 50,000 POS terminals. This organization provides robust payment solutions across diverse sectors, ensuring seamless financial transactions and services.

The sprawling operations generated a torrent of data, scattered across disparate systems and often inconsistent, lacking necessary metadata for effective analysis. The consequences were far-reaching, including:

• Manual Processes: Dominated data operations, consuming valuable resources.

• Inconsistent Data: Hindered time-to-insight and critical business analysis.

• Inaccessible Insights: ATM performance, cash management, and digital initiatives remained unanswered.

• Error-Prone Reconciliation: Time-consuming revenue reconciliation across divisions.

The organization possessed a goldmine of data but lacked the tools to extract its full value.

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To address these challenges, Exponentia.ai and the organization embarked on a journey to create a unified Data Lake. The solution involved:

• Data Quality and Consistency: Establishing robust data quality checks and metadata management to ensure data reliability and consistency.

• Robust Data Ingestion: Automating the ingestion of data from over 30 databases and Excel files into a centralized cloud-based repository.

• Scalable Data Architecture: Implementing a scalable architecture capable of handling data from multiple countries, ensuring efficient data access, partitioning, and indexing.

• Advanced Analytics : Developed interactive dashboards that provided actionable insights into key areas such as ATM performance, cash operations, and P&L analysis, enabling data-driven decisions across the organization.

• Automated Workflows: Streamlining operations and reducing manual intervention. For example, the process of generating daily ATM performance reports was automated, reducing manual effort by 70% and enabling faster identification of performance issues.

• Improved Data Quality and Consistency: Centralized metadata and data quality checks significantly enhanced data reliability, enabling more accurate analysis.

• Data-Driven Decision Making: Interactive dashboards provided real-time insights into ATM performance, cash management, and digital initiatives, empowering data-driven decision-making.

The Data Lake initiative yielded impressive results:

• 200+ Man-Hours Saved Monthly: Automated data ingestion and processing saved over 200 man-hours per month, allowing resources to focus on strategic initiatives.

• ₹2 Crores Annual Revenue Optimization: Automated P&L calculations improved accuracy, identifying potential revenue leakage of over ₹2 crores annually.

• ₹4 Crores Annual Cost Savings: Streamlined operations and reduced manual efforts led to estimated cost savings of over ₹4 crores annually.

• Improved Data Quality and Consistency: Centralized metadata and data quality checks significantly enhanced data reliability, enabling more accurate analysis.

• Enhanced Decision-Making Capabilities: Interactive dashboards provided real-time insights into ATM performance, cash management, and digital initiatives, empowering data-driven decision-making.