Integrated Big Data Architecture and Low-Code Business Automation Solution

The organization operates numerous dispersed systems across the world, generating approximately 10 terabytes of disparate data monthly, including fleet, HR, customer service, and sales data. This fragmentation hampers timely decision-making, manual reporting is time-consuming, and operational inefficiencies persist due to lack of integrated data architecture and automation solutions. The organization seeks to implement flexible, scalable digital tools to automate core processes and leverage Big Data analytics for strategic advantages.

A global transportation and travel enterprise managing extensive fleet operations, passenger services, and vendor relationships, seeking to optimize data processing and operational workflows.

• Design and implement a robust Big Data architecture capable of processing over 10 terabytes of data monthly, integrating more than 30 disparate data sources.
• Develop a scalable data pipeline supporting both full and incremental (delta) processing for efficient data flow and analysis.
• Establish a Lakehouse storage architecture to enable advanced Business Intelligence and machine learning capabilities.
• Migrate existing data platforms (e.g., Snowflake to Databricks) to optimize processing time and cost efficiency.
• Create reliable analytical models to generate insightful reports, supporting data-driven decision-making.
• Implement cloud and on-premises data storage solutions ensuring 99.9% availability and secure data management.
• Enhance operational efficiency for field and shore teams through Low-Code applications, saving up to 250 hours per full operational cycle.
• Develop automated workflows utilizing DevOps best practices for continuous integration, deployment, and infrastructure management.
• Design and deploy Low-Code apps to automate repetitive tasks such as voyage reporting, project request submissions, and vendor onboarding, improving process speed and accuracy.

• Data pipelines supporting ingestion from databases, REST APIs, CSV, and JSON files into a centralized repository.
• Implementation of a Lakehouse storage architecture for unified data access and processing.
• Migration strategy supporting platform changes such as Snowflake to Databricks, ensuring minimal downtime.
• Analytical models generating insights for financial and operational decision-making.
• Cloud and on-premises infrastructure optimized for scalability, security, and cost-efficiency.
• A smart API for external system data sharing compliant with relevant legal and privacy standards.
• Automated deployment and infrastructure management based on DevOps principles, including CI/CD pipelines, IaC using declarative languages, and observability tools.
• User-friendly Low-Code applications for operational efficiency: voyage reports, project requests, vendor onboarding, and other automation workflows.

• Connecting data sources such as databases, REST APIs, and flat files to centralized data repositories.
• External systems for secure data sharing via APIs.
• Legacy systems requiring integration during migration and automation.

• Support processing of over 10 terabytes of data monthly with high reliability and fault tolerance.
• Achieve 99.9% system uptime and data security compliance.
• Enable real-time or near-real-time data processing and reporting.
• Ensure scalable infrastructure capable of handling increasing data volume and user demand.
• Automate deployment processes to reduce human error and deployment time.

The implementation of this integrated data architecture and automation ecosystem aims to significantly enhance decision-making capabilities through timely, insightful analytics. Automated workflows and Low-Code applications are expected to save up to 250 hours per fleet voyage for managerial staff, streamline processes such as vendor onboarding and project requests, and improve operational agility. Overall, these improvements will lead to increased efficiency, reduced manual effort, better cost management, and a stronger competitive position in the global transportation and travel sector.