Executive Summary

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 modernize 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 specialized 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.

Key Results and Benefits

1. Advanced Data Processing: 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, 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:

1. 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.
2. Current System Limitations:
   The existing SQL-based data warehouse struggled with scalability and flexibility & ROImaking it difficult to handle large datasets and deliver timely insights.
3. Data Quality and Governance:
   As the volume and complexity of data grew, maintaining consistent quality and implementing robust governance became a significant challenge.
4. Technology Adoption:
   Accelerating the adoption of Databricks and 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.

Testimonial