Optimizing Data Ecosystems for a Global Technology Giant

About the Client

The client, a Global Technology Giant, operates large-scale platforms supporting Maps Services and Marketing and Advertisement Systems, catering to billions of users worldwide. To maintain efficiency, performance, and accuracy in these platforms, the client required robust data ingestion pipelines and a scalable Cloud and DevOps infrastructure. Additionally, the client sought support in managing their vast data ecosystems with a skilled team of Data Stewards. Enshire was selected as the trusted partner to build the solution, providing expertise across multiple geographies.

Requirements

• Scalable Data Pipelines: Build highly efficient data ingestion pipelines to handle massive volumes of real-time and batch data.
• DevOps Automation: Streamline infrastructure and deployment processes to enhance scalability, reliability, and speed-to-market.
• Data Quality and Governance: Provide a team of Data Stewards to manage, monitor, and ensure data consistency and compliance.
• Geographical Collaboration: Establish agile teams across Malmo and Paris to facilitate global operations and on-time delivery.

Solution

• Data Ingestion Pipelines: Enshire developed robust data ingestion pipelines to process high volumes of structured and unstructured data efficiently.
• DevOps Infrastructure: To enable seamless integration, deployment, and scalability, Enshire established a comprehensive Cloud and DevOps infrastructure.
• Team of Data Stewards: Enshire deployed a dedicated team of Data Stewards to monitor, manage, and ensure data quality across the client’s systems.
• Geographically Distributed Teams: Teams were set up in Malmo (Sweden) and Paris (France) to provide around-the-clock coverage and meet global operational requirements. Implemented agile methodologies to ensure seamless collaboration across teams, enabling faster delivery and alignment with project goals.

Benefits

• Improved Data Ingestion Performance: The new pipelines processed 40% more data with improved speed and accuracy, reducing ingestion times for both batch and real-time workflows.
• Efficient DevOps Workflows: Automated DevOps pipelines accelerated deployment cycles by 60%, improving speed-to-market for new updates and features. Kubernetes-based orchestration ensured 99.9% uptime and reduced downtime during critical deployments.
• Enhanced Data Quality and Governance: With the Data Stewards team in place, data errors were reduced by 35%, ensuring high-quality, validated datasets for Maps and Marketing Systems.
• Scalability and Fault Tolerance: The cloud-native infrastructure provided the ability to scale dynamically during traffic spikes, ensuring seamless operations for billions of users.
• Global Collaboration: Teams in Malmo and Paris delivered consistent and collaborative results, enabling the project to stay on track and meet client objectives efficiently.

Technologies Used

• Data Ingestion: Apache Spark, Scala, Java.
• DevOps Pipeline: Gradle, Jenkins, Python, Kubernetes.
• Infrastructure: Cloud-native architecture with Kubernetes for scalability and fault tolerance.