Seamless Data Integration with Snowflake and AWS for a Leading Gaming Brand

About the Client

Supply Medium is a data-driven organization focused on delivering innovative technology solutions and reliable data services. The company leverages modern cloud platforms and analytics to streamline operations, improve decision-making, and support business growth across multiple industries.

The Background

As Supply Medium continued to expand and evolve, the organization recognized the need for a more advanced data platform. This transition was critical for streamlining operations, improving efficiency, and leveraging data analytics to make smarter decisions, ensuring long-term success in a competitive market.

The Challenge

Supply Medium faced a significant challenge in integrating data from a newly launched platform into its existing Enterprise Data Warehouse (EDW) on Snowflake while smoothly transitioning to a modern data ecosystem. Several factors made this integration complex:

• Time Sensitivity: The data migration and integration needed to be completed quickly to avoid business disruptions.
• Resource Constraints: The internal team lacked the bandwidth and expertise required for a smooth and efficient transition.
• Data Structure Differences: The new platform’s data model required careful transformation to align with the existing EDW.
• Data Accuracy: Ensuring data consistency between source and target systems was critical for maintaining high-quality analytics and reliable insights.
• Lack of Familiarity: Since the platform was newly implemented, the team had limited knowledge of its data structures.

Given the complexity of the task, Supply Medium partnered with our team to ensure a seamless, quick, and efficient transition.

The Solution

Our team devised a structured and scalable data integration strategy, leveraging AWS services and Snowflake to ensure a smooth, risk-free migration. By adopting an Agile methodology, we maintained an iterative and collaborative approach, allowing for continuous improvements, quick adaptations to unforeseen challenges, and seamless stakeholder alignment. This ensured that the integration remained efficient and responsive to evolving requirements.

1. In-Depth Analysis & Strategic Planning

• Analyzed the new platform’s database and existing EDW to identify schema differences and key dependencies.
• Mapped data fields, transformations, and relationships to ensure seamless compatibility with the existing Snowflake data warehouse structures.
• Designed a structured data pipeline architecture to enable smooth integration.

2. Data Engineering & Pipeline Development

• Built ETL (Extract, Transform, Load) data pipelines from the source system.
• Used AWS DMS (Database Migration Service) for efficient data migration to Amazon S3.
• Leveraged Amazon S3 as an intermediate data lake for storage.
• Utilized dbt to structure and transform data from staging to the operational data source before integrating it into the EDW.
• Used Apache Airflow for pipeline orchestration, enabling automated updates every 15–30 minutes for near real-time data availability.
• Developed SQL stored procedures for complex transformations, ensuring data integrity and adherence to business rules.

The Results

• Supply Medium’s data was successfully integrated into Snowflake without disruptions, ensuring business continuity.
• Near real-time data updates enabled faster data-driven insights and improved strategic decision-making.
• Centralized, accurate analytics empowered stakeholders with better reporting efficiency.
• AWS services minimized operational costs while handling increased data volume without excessive infrastructure expenses.
• A flexible pipeline architecture allowed easy integration of future data expansions and additional data sources.

Post-Implementation Support & Knowledge Transfer

To ensure a seamless transition, we provided extensive post-integration support, enabling Supply Medium’s team to manage the system independently.

• Provided two months of post-integration support to resolve early-life technical issues and optimize performance.
• Conducted Knowledge Transfer (KT) sessions with hands-on training for managing, troubleshooting, and optimizing data pipelines.
• Facilitated reverse KT sessions to identify and address any remaining knowledge gaps.

Client Feedback

Supply Medium appreciated our technical expertise, adaptability, and proactive approach. The team was recognized for navigating complex challenges, maintaining transparent communication, and delivering high-quality results on time.