Optimizing Airlines with Insights Analytical Tool

Industry

Aviation & Data Analysis

Technologies

javaspringangularelasticteradata

Country

United States

Client Overview

Insights is a web tool designed to simplify and speed up research and analysis 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. Its risk-tracking features streamline risk management, auditing and collaboration, helping with 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

Efficient Data Procession & Search

Clear Data Visualization

Clear Data Visualization

Enhanced Passenger Data Analysis

Enhanced Passenger Data Analysis

System Development

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 data visualization layer that surfaces what is buried in airline data, so the decision-making team can interpret and analyse it.

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

  1. 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.

  2. Designing a Java/Spring backend based on a microservices architecture that was capable of processing and searching through large volumes of data.

  3. Designing and creating an Angular-based frontend application for search and visualizations of analytical data related to passengers, flights, audits, and airline risks.

  4. 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.

  5. 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 used to implement the backend architecture, using its dependency injection, aspect-oriented programming, and modular design, which fit the microservices architecture well.

Elasticsearch: Provided search across large volumes of data. Its distributed nature and real-time search and analytics fit the Insights project well.

Angular: The frontend framework, used to build a 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: Stored the large analytical datasets on passengers, flights, audits and airline risks. Its parallel processing and support for complex queries suited the project's analytical needs.

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 close, adaptable way of working let us deliver a solution that clearly improved research and risk management at 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."

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