Executive Summary
A multinational mass media and entertainment company encountered hurdles in collecting customer information to make strategic decisions. To tackle this challenge, they undertook an initiative to transform its data architecture. The conglomerate, recognizing the pivotal role of data in strategic decision-making, worked towards creating a unified and scalable data platform. The aim was to establish a robust foundation for data-driven insights. The project’s focal point was the creation of a 360-degree customer view, optimizing data from various sources for enhanced analytics.
This transformation was not merely a technological upgrade; it signified a paradigm shift in how the conglomerate approached data. The implementation of the Strategic Options Development and Analysis (SODA) framework, coupled with strategic automation using tools like Postman, Oracle Database, and MariaDB, ensured data accuracy and quality. The conglomerate successfully addressed the challenge of disparate data sources, streamlining the data ingestion and ETL processes.
About the Client
A prominent entertainment conglomerate, the client offers a diverse range of entertainment merchandise, interactive gaming experiences, and captivating literary works. Their overarching mission revolves around elevating the resonance of the esteemed company’s cherished characters and narratives, meticulously transforming them into tangible and engaging realities. Its innovative endeavors serve as a conduit for the company’s ethos and creativity, profoundly impacting its audience.
Business Challenge
Faced with disparate data sources, the multinational mass media and entertainment conglomerate encountered hurdles in aggregating and unifying customer information. The decentralized architecture led to fragmented insights, impacting personalized experiences and strategic decisions.
The existing silos impeded operational efficiency, hindering the conglomerate’s ability to derive comprehensive insights from its diverse data streams. This challenge prompted the need for a centralized data platform to streamline data integration and provide a holistic view of customer data, driving informed decision-making and enhancing overall operational efficiency.
Our Solution
To address the intricate data challenges, Factspan focused on creating a dynamic business and customer data platform, enabling a 360-degree view of customer interactions. Leveraging advanced tools, including AWS Glue, DMS, Kinesis, Lambda, and Snowflake, the company revamped its data architecture.
The revamped architecture involves the extraction of data from various sources, including RDBMS and event-based systems, using AWS Glue jobs and NiFi with RabbitMQ processor.
The transition from AWS Glue to AWS DMS facilitated efficient data contract generation and laid the foundation for building a Snowflake data warehouse using DBT tools.
Key to the solution is the implementation of a unified consumer experience (UCE) platform, aptly named ‘Guest 360’. This platform combines diverse data sources into a cohesive structure, providing enriched, cleansed, and normalized datasets. The implementation of Snowflake objects like streams, tasks, and DBT tools ensures a near real-time data pipeline for loading UCE data.
The architecture’s transformative power lies in its ability to consolidate data, ensuring a single source of truth for guest insights. By unifying data pipelines and creating a centralized data warehouse, the solution enhances the conglomerate’s decision making capabilities, operational efficiency, and lays the groundwork for future enhancements. The solution guarantees the organization’s adaptability to evolving business needs and positions the company for sustained success in the dynamic entertainment landscape.
Business Impact
- Enhanced data access speed by 60% for faster insights
- Achieved 30% cost savings in maintenance with new architecture
- Centralized data, unifying 65 sources effectively
- Positioned the organization for 40% faster future integrations
- Accelerated data processing, ensuring operational efficiency