Enhancing Data Processing and Operational Efficiency: A RightShip Success Story
RightShip, an ESG-focused digital maritime platform with 200+ employees headquartered in Malta, partnered with Eunoia from 2021 to modernise its data infrastructure using Databricks. The engagement covered four years of Databricks implementation and maturity: initial capacity support in 2021, full Lakehouse Architecture transition in 2022, first ML model deployment in 2023, and continued innovation scaling into 2024 and beyond. Six key results were achieved: advanced data processing via a Databricks-powered Lakehouse Architecture, a scalable resource model, embedded governance through medallion-layered architecture and data lineage tracking, 12 Databricks-certified professionals trained across data and AI engineering teams, accelerated delivery of critical use cases, and two ML models deployed via MLOps. Paul Said, Chief Data Officer at RightShip, described Eunoia as an integral part of their team.
RightShip, a leader in maritime risk management, launched a transformative initiative aimed at enhancing safety and operational efficiency. The primary business goal was to leverage advanced analytics and data management tools, including Databricks, to modernise its data infrastructure and improve decision-making across vessel operations.
To accelerate this transformation, RightShip sought a boutique consultancy that could align top talent with the company’s objectives. The key driver behind the investment was the need for specialised data engineering and data science expertise to fully harness the potential of Databricks and its capabilities.
By leveraging Eunoia’s expertise, RightShip improved its ability to assess vessel performance and environmental impact while ensuring compliance with international safety regulations.
These enhancements have led to increased operational efficiency and solidified RightShip’s position as a leader in maritime risk management.
Transitioned from a traditional SQL-based data warehouse to a Databricks-powered Lakehouse Architecture, enabling reusable data products and timely analytics.
2. Scalable Resource Model:
Eunoia provided flexible support, allowing RightShip to scale its resources up or down based on project needs.
3. Embedded Best Practices:
Implemented frameworks like the medallion-layered architecture and data lineage tracking, enhancing data quality and governance data quality and governance, bridging between several data teams within the company.
4. Upskilled Team:
With the help of Eunoia, RightShip developed a strong internal team, with 12 Databricks-certified professionals, allowing the company to scale their data estate further, making sure that what they are building is future proof.
5. Accelerated Delivery:
Due to Eunoia’s experience and agility to implement a foundation based on best practises, it was easy for the rest of rightship teams to build on this foundation delivering Critical use cases were faster due to streamlined processes.
6. Strategic AI Foundation:
With the help of Eunoia, Rightship deployed two machine learning model using ML Ops, establishing the groundwork for future AI initiatives in a very short amount of time which was not achievable if Rightship’s resources did it themselves on their own.
Company Overview
Name: RightShip Industry: ESG focused digital maritime platform Headquarters: Malta
– Size: 200+ employees
The Challenge
RightShip faced multiple interrelated challenges that required an effective and immediate solution:
Short-Term Capacity Issues:
Recruiting and upskilling talent was challenging, especially when implementing a critical data project that required specialised skills in data engineering and analytics.
Current System Limitations:
The existing SQL-based data warehouse struggled with scalability and flexibility & ROI making it difficult to handle large datasets and deliver timely insights.
Data Quality and Governance:
As the volume and complexity of data grew, maintaining consistent quality and implementing robust governance became a significant challenge.
Technology Adoption:
Accelerating the Databricks implementation and adoption of other advanced frameworks required external expertise to achieve operational maturity.
The Solution
Eunoia provided a tailored approach to meet both RightShip’s immediate and long-term needs:
Elastic Capacity Support
Eunoia allocated skilled resources to address RightShip’s short-term capacity issues, providing scalable support to meet project requirements.
Modern Data Architecture
Eunoia brought a very solid foundation of knowledge related to best practises to transition RightShip to a Lakehouse Architecture built on Databricks and Delta Lake, dealing with data governance, scalbability & performance issues and being AI ready.
Bringing experience to the table
Eunoia’s resources were bringing knowledge and frameworks related to different topologies and verticals. Having Eunoia guiding Rightship on what needs to be done best on their experience with clear examples helped us to accelerate and achieve a faster ROI by not doing mistakes in our data journey.
Team Training and Upskilling
Empowered RightShip’s internal team through hands-on training, and guidance resulting in more than 12 Databricks-certified professionals in different team ranging from data engineers to AI engineers capable of managing data operations independently.
Timeline
– 2021: Initial engagement and short-term capacity support.
– 2022: Transition to Databricks and implementation of the Lakehouse Architecture.
– 2023: Databricks maturity achieved, first ML model deployed.
– 2024 and beyond: Continued collaboration, focusing on innovation and scaling operations.
Results
Quantitative Results
Certified Professionals: 12 team members achieved Databricks certifications, equipping RightShip for sustained success. Operational Efficiency: Accelerated project delivery and reduced time-to-market for critical use cases.
Qualitative Results
Enhanced Data Quality: Frameworks like medallion-layered architecture and lineage tracking embedded governance and reliability across operations. Improved Scalability: The elastic resource model provided the flexibility to scale dynamically with project demands. Operational Independence: Upskilled staff making sure that Eunoia’s quality in the foundation delivery is also delivered by Rightships internal resources ensuring scalability.
Eunoia has become an integral part of RightShip, seamlessly augmenting our team and enabling us to scale capacity as needed. Their expertise in Databricks has been instrumental in modernising our data operations and embedding best practices across our workflows. The partnership has transformed how we manage data, ensuring we deliver timely, high-quality insights to support our mission of a safer, more sustainable maritime industry.
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Industry: ESG focused digital maritime platform
Short-Term Capacity Issues:
