[About]
Data Transformation
Assisting a leading telematics provider in modernising its infrastructure and technology to enhance customer support and improve efficiency.
/ Industry: Telematics
/ Technologies: React, Data, Java, Node.js, MariaDB, MySQL, AWS: Aurora MySQL, ElastiCache with Redis, EC2, ELB, Kafka
/ Service: Data Transformation
The client provides data-driven telematics and asset monitoring solutions for mission-critical clients across the UK, incl. blue light services like Ambulance Trusts and Gatwick Airport. Their offerings include Insight Telematics, Asset Monitoring, and vehicle CCTV, helping businesses optimize fleet performance, enhance security, and improve operational efficiency.
The client faced a challenge with their existing technologies, which were preventing the company from achieving two key goals: designing a data architecture that could easily accommodate their growth and streamlining data processes to improve efficiency and optimize resource utilisation. To address these challenges, Godel was chosen to enable the client to leverage the required expertise in designing and implementing complex data platforms.
[Our approach]
Godel conducted AS-IS business and architecture overviews, collecting pain points and opportunities for improvement, coupled with the understanding of business strategy goals and aspirations to provide them with a roadmap for the future. The team additionally gathered TO-BE requirements, prioritising recommendations using an evaluation framework and building an effort/value matrix, defining the TO-BE data architecture.
Finally, a migration/transformation plan was produced, exploring infrastructure options with cost representations for the TO-BE solution, along with a delivery plan and high-level backlog with estimates, proposing a team composition.
[Outcomes]
The project was a success, with the Godel team laying a solid foundation for a development team. The outputs supported a business case to secure funding approval for the development phase. It also provided the client with a a comprehensive understanding of the platform’s scope, cost, scale and comparison of established technologies within Big Data, to ensure the platform is built correctly, creating a blueprint for the system’s future development.