Integrated Data Analytics and Security Monitoring Dashboard

[Audio] My name is Eric Ocansey, and I will be presenting my MS-CISBA capstone project titled Integrated Data Analytics and Security Monitoring Dashboard. This project focuses on combining business analytics, data management, software systems, and cybersecurity monitoring into one centralized platform capable of supporting operational awareness and informed decision-making. The system was developed using Python, Streamlit, SQLite, pandas, Plotly, and supporting analytical technologies..

[Audio] Modern organizations generate large amounts of operational and system activity data every day. However, this information is often distributed across separate systems, making it difficult to analyze performance and monitor security events efficiently. The goal of this project was to create a unified platform where organizations can visualize business performance while simultaneously monitoring suspicious system activity and operational risks. The dashboard supports KPI reporting, trend analysis, event monitoring, and centralized data visibility within a single environment. By integrating analytics and monitoring together, the system improves operational awareness and provides a more complete view of organizational activity..

[Audio] One of the major challenges organizations face today is fragmented data environments. Business analytics systems and cybersecurity monitoring tools are commonly implemented independently, which limits visibility and delays response to operational or security-related issues. This fragmentation can lead to inconsistent reporting, slower decision-making, and reduced ability to detect abnormal activity in real time. The project addresses this challenge by demonstrating how a centralized analytical platform can combine operational intelligence with security monitoring capabilities. The result is a more efficient and integrated approach to organizational analytics and monitoring..

[Audio] The primary objective of this project was to develop a centralized dashboard capable of integrating analytics and security monitoring into one platform. The system was designed to: visualize business KPIs and trends, monitor suspicious login activity, track abnormal events, manage structured datasets, and demonstrate the integration of multiple MS-CISBA curricular areas. The final prototype combines analytics processing, software engineering, database management, and cybersecurity concepts within a single working application..

[Audio] The project was implemented using several modern technologies that support analytics processing and interactive visualization. Python was used as the primary programming language because of its flexibility and strong support for analytics libraries. Streamlit was used to build the dashboard interface and provide an interactive user experience. SQLite was selected as the database system for structured data storage and efficient querying. pandas was used for data processing and transformation, while Plotly provided interactive visualizations and charts. Additional technologies included SQLAlchemy for database integration, scikit-learn for anomaly detection preparation, and GitHub for version control and portfolio management. Together, these technologies support modular development, scalability, and analytical processing..

[Audio] The executive dashboard provides a centralized summary of organizational performance and monitoring information. Key metrics, alerts, and trend indicators are presented in a clear and accessible format designed for rapid interpretation. The dashboard combines operational KPIs with monitoring indicators so that users can evaluate business performance while remaining aware of system activity and potential security concerns. The design emphasizes usability, visibility, and executive-level reporting..

[Audio] The analytics component processes operational datasets and transforms raw information into meaningful business insights. The system generates revenue trends, performance metrics, KPI summaries, and category analysis through interactive visualizations. These charts allow users to explore patterns within the data and evaluate organizational performance more effectively. This part of the project demonstrates Business Analytics concepts by showing how analytical processing and visualization can support strategic and operational decision-making..

[Audio] The platform also includes integrated cybersecurity monitoring capabilities. The monitoring engine analyzes authentication activity, suspicious IP addresses, failed logins, and abnormal system behavior. Risk indicators and warning alerts help identify activities that may require investigation or administrative attention. Integrating security monitoring directly into the analytical environment improves operational awareness and demonstrates how cybersecurity concepts can support enterprise analytics systems..

[Audio] Authentication activity is analyzed over time to identify unusual behavior patterns and potential security risks. The system tracks repeated failed logins, abnormal login frequencies, and unusual access behavior that may indicate suspicious activity. Interactive visualizations improve interpretability and help administrators identify patterns more quickly and efficiently. This demonstrates how analytical techniques can support proactive cybersecurity monitoring and risk management..

[Audio] Login activity heatmaps and event distribution analytics provide additional visibility into system behavior. The heatmaps help identify unusual login times, spikes in activity, and irregular usage patterns across different periods. The system also categorizes events such as successful logins, failed authentication attempts, password changes, and suspicious events. These visualizations improve situational awareness and support more effective monitoring of operational environments..

[Audio] The platform maintains detailed records of operational and security-related events. Information such as usernames, IP addresses, timestamps, event types, and device information is stored and analyzed within the system. This centralized visibility helps administrators investigate suspicious activity, review user behavior, and monitor system operations more effectively. The integration of structured event storage with monitoring capabilities reflects both Data Management and Cybersecurity principles..

[Audio] Data management plays a foundational role within the project architecture. The platform supports dataset uploads, validation, inspection, querying, and structured storage using a centralized SQLite database. Efficient data organization supports both analytics processing and monitoring operations. The database layer ensures that business and security information can be retrieved consistently and processed efficiently throughout the system. Next we look at the Snapshots of the implementation done..

[Audio] Application logging supports operational visibility, auditing, debugging, and system maintenance. The platform records system events, analytics activity, database operations, and monitoring events in centralized logs. These logs improve traceability and contribute to cybersecurity awareness by maintaining historical records of system behavior. Logging functionality is an important component of enterprise-grade monitoring systems..

[Audio] The project demonstrates how analytics, monitoring, database management, and software engineering can work together within a unified environment. The architecture supports centralized processing, modular development, and scalable integration of multiple components. Combining these capabilities into one platform improves visibility and demonstrates the interdisciplinary nature of enterprise information systems..

[Audio] The system also includes authentication functionality designed to simulate secure access management. Role-based access concepts help demonstrate how enterprise systems protect sensitive organizational data and control access to analytical information. Authentication features reflect the integration of cybersecurity principles with software system development.

[Audio] This project demonstrates synthesis across four major MS-CISBA curricular areas. Software Systems is represented through the development of the modular dashboard architecture and integrated application environment. Business Analytics is demonstrated through KPI analysis, trend analysis, and interactive visual reporting. Data Management is reflected through database storage, structured datasets, querying, and data organization. Cybersecurity and Networking concepts are demonstrated through suspicious activity monitoring, authentication analysis, and event tracking. The integration of these areas into a single system reflects the interdisciplinary skills required in modern enterprise environments..

[Audio] Several enhancements could improve the platform in the future. Potential improvements include: cloud deployment using AWS or Azure, real-time streaming analytics, machine learning-based anomaly detection, advanced role-based access control, and scalable enterprise database architecture. These additions could transform the prototype into a production-ready enterprise analytics and monitoring platform..

[Audio] In conclusion, this project successfully demonstrates the integration of analytics and cybersecurity monitoring within a unified dashboard environment. The platform combines Software Systems, Business Analytics, Data Management, and Cybersecurity concepts into a practical enterprise-oriented solution. The system improves operational visibility, supports proactive monitoring, and demonstrates how centralized analytics platforms can enhance organizational decision-making. The project also demonstrates strong potential for future scalability and enterprise implementation. Thank you very much for your time and attention..