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Real-time monitoring of financial transactions and user behaviour to identify fraudulent activities.
Tracking and analysing user interactions on websites or mobile apps to optimise user experience.
Identifying unusual patterns or events in data streams to signal potential issues or opportunities.
Organizations often struggle with :
These issues necessitate a robust, scalable, and real-time processing solution.
The proposed solution leverages AWS services to create a security data bridge that ensures secure, efficient ingestion, processing, and analysis of real-time events. The architecture is designed to handle large volumes of streaming data, ensuring scalability, reliability, and low latency. Key components include:
Streamlined ingestion and processing of data with minimal delay.
Architecture designed to accommodate varying data volumes.
Predefined rules and machine learning models for threat detection.
Centralised storage in Amazon S3 with lifecycle management.
Logs and metrics for performance tracking and issue detection.
Real-time data streaming and ingestion.
Serverless transformations and processing scripts.
Reliable messaging for data flow management.
Secure, scalable storage with lifecycle policies.
Data transformation, ETL workflows, and threat detection.
Logging and auditing of AWS activities.
The solution is hosted entirely on AWS, utilising serverless and managed services to ensure:
The implementation team includes :
Ongoing support includes :
A dedicated team ensures :
This project successfully demonstrates the power of real-time data streaming and processing, delivering immediate and actionable insights. By implementing the Security Data Bridge, the organisation benefits from enhanced security, optimised user experiences, and operational efficiency. The architecture’s scalability and flexibility allow for future enhancements, such as integration with advanced AI/ML models for predictive analytics.