Optimizing Airlines with Insights Analytical Tool
Industry
Duration
Team
Technologies
Client Overview
Insights is a powerful web tool designed to simplify and accelerate research and analysis activities within an airline, handling the complex data that is constantly updated every second. It enables users to search and navigate data without writing SQL queries, making it accessible to all staff. With robust risk-tracking capabilities, Insights streamlines risk management, auditing, and collaboration, adding significant value by enhancing proactive risk handling and regulatory compliance. Since its deployment, Insights has been crucial for airline analysts, providing real-time insights and optimizing resource utilization. One notable achievement was its role in managing overbookings, saving the airline several million dollars through optimized booking processes.
Client Needs
Efficient Data Procession & Search
Clear Data Visualization
Enhanced Passenger Data Analysis
System Development
The client's needs centered around developing a solution that could efficiently process and visualize extensive datasets related to passengers, flights, audits and airline risks. They required a system that could adapt to the evolving demands of the airline industry.
Services Provided
Big Data: Our data team assisted with the initial data analysis and the creation of a comprehensive data warehousing solution.
Data Visualization: Our team designed a high-impact data visualization layer to unlock the knowledge hidden in airline data, making it easier for the decision-making team to interpret and analyze critical information.
Backend Development: We designed and developed a backend based on Java and Spring using a microservices architecture to handle the huge volumes of airline data.
Frontend Application Development: Development of an Angular-based frontend application for data search, visualization and audit management.
Customer Detection Algorithm: Research and development an algorithm to identify and unify airline passengers using residual data from various sources.
Scope of Work
Designing data visualization using D3 library for comprehensive and interactive graphs, enabling dynamic visualization of complex datasets. This allowed us to build custom, data-driven visual representation of passengers, flights and risks data that enabled in-depth analysis.
Designing a Java/Spring backend based on a microservices architecture that was capable of processing and searching through large volumes of data.
Designing and creating an Angular-based frontend application for search and visualizations of analytical data related to passengers, flights, audits, and airline risks.
Engaging in ongoing cooperation with our client, including continuous development of new features to adapt to the constantly evolving business needs of airlines and incorporating feedback from the analysts' team. Utilizing machine learning to support the risk detection process in airlines and employing LLM large language model to assist analysts in finding information within large datasets.
Researching and developing an algorithm to identify and unify airline passengers based on residual data from different sources.
Technologies Used
Java: Java was chosen as the primary programming language for backend development due to its reliability, scalability, and extensive ecosystem of libraries and frameworks.
Spring: The Spring framework was utilized to implement the backend architecture, leveraging its features for dependency injection, aspect-oriented programming, and modular design, which aligns well with microservices architecture.
Elasticsearch: Elasticsearch was integrated into the system to provide advanced search capabilities across large volumes of data. Its distributed nature and support for real-time search and analytics made it a suitable choice for the Insights project.
Angular: Angular was selected for front-end development to create a dynamic and responsive user interface. Its component-based architecture, two-way data binding, and extensive support for building single-page applications (SPAs) made it ideal for implementing the search and visualization features required by the client.
Teradata: Teradata was utilized for large analytical data storage, providing a robust and scalable solution for handling huge datasets related to passengers, flights, audits and airline risks. Its parallel processing capabilities and support for complex queries made it well-suited for the analytical requirements of the Insights project.
Development Process
Our development process involved close cooperation with the client to understand their needs and continuously adapt the system to their evolving requirements. We began with a series of workshops with the client to understand the intricacies of the aviation industry and familiarize ourselves with their complex data. Following these workshops we employed agile methodologies to ensure iterative development and timely delivery of features. Regular feedback from the client’s analysts was crucial in refining the functionalities. This collaborative and adaptable approach empowered us to deliver a solution that markedly enhanced the efficiency of research and risk management activities within the airline. Upon witnessing Insights' ability to instantly display the history of intricate eTicket exchanges, the Internal Audit Manager remarked: "We have accomplished in 3 minutes what used to consume an entire afternoon."
common.checkClutchWork