Swisscom Blue TV Analytics Journey Into AWS Cloud
Modernized, cost-effective and scalable infrastructure
Swisscom Optimizes TV Analytics by Migrating to the AWS Cloud
An outdated data warehouse infrastructure slowed down Swisscom's TV analytics processes — time for new solutions! Together with b.telligent, the migration to a cutting-edge, scalable solution in AWS Redshift was implemented. The result: optimized data analytics, improved performance, and seamless integration with the cloud.
Quick Facts About the Project
Location & Sector: Switzerland, telecommunications & media
Company size: Large company
Project duration: 13-18 months
Project type: Migration project
Technology: AWS
Initial Situation
Swisscom is Switzerland's leading telecommunications provider, offering services in mobile, fixed network, internet, TV, and comprehensive IT services. Known for its innovation, Swisscom heavily invests in the country's digital infrastructure. Swisscom's blue TV offering provides a broad selection of live channels, on-demand content, and streaming services. With features like time-shifted viewing, recording, and personalized recommendations, it offers a modern, converged, and integrated entertainment experience. To provide the best possible TV service to its customers, Swisscom leverages advanced analytics to enhance the overall user experience and ensure service stability. The foundation for these analytics was an on-premises data warehouse (DWH) supporting reporting, machine learning models, and advanced analytics, including anomaly detection and other AI-driven insights.
Goals and Motivation
The project aimed to transition the on-premises TV Data Warehouse to AWS Redshift, in line with Swisscom's strategic move to establish AWS as its primary cloud provider. For its AWS migration, Swisscom relied on the expertise of b.telligent, primarily because of its extensive experience in DWH migrations, proficiency in AWS, and strong capabilities in data, analytics, and AI.
Drivers of This Migration for Swisscom
Infrastructure Modernization and Cost Efficiency
- Costreduction
- Replacingon-premises infrastructure with an cloud-based solution by AWS
- Reducing complexity
Performance and Innovation
- Increased efficiency and enhanced scalability
- Enabling innovation and accelerating the pace of innovation
Obstacles and Challenges
- A defined deadline to avoid the license renewal of the existing solution.
- Business-critical workloads had to be on schedule: Ensure that key workloads were operational by the specified timeline.
- Dependencyon services in the new AWS region Europe (Zurich). As the AWS Zurich region wasbeing set up, the project timeline had to be aligned with the availability ofAWS services in this region.
Solution
After an in-depth architecture workshop, Swisscom successfully migrated the existing data warehouse to AWS Redshift. This complex migration involved optimizing and transferring all ETL and ELT processes.
New frameworks were developed to integrate data sources and sinks, while an automated framework was built to streamline the creation and delivery of data exports and Excel reports using Python and AWS Lambda. Additionally, a new orchestration solution was implemented in Redshift to improve efficiency. Statistical models for anomaly detection in time series data were migrated to Redshift and Lambda, while machine learning models were re-implemented in Redshift and SageMaker AI.
This included the development of a multi-class classification model using SageMaker AI, with inference seamlessly integrated back into Redshift via Redshift ML. This comprehensive transformation not only ensured the scalability and performance of Swisscom’s data operations but also paved the way for future innovation in its analytics capabilities.
Project Migration Steps to AWS Cloud
- Definition and setup of the overall architecture of the target solution in AWS.
- Code Migration: Transition of the existing code base, including all ETL/ELT processes.
- Data Migration: Migration of existing data to AWS, ensuring continuity and integrity throughout the process.
- ML Model Migration: Transfer of machine learning models to AWS, maintaining full functionality and performance.
- Export Job Migration: Migration of export jobs critical for business reporting and operational needs.
- Real-Time Anomaly Detection: Relocation of real-time anomaly detection systems, ensuring uninterrupted monitoring capabilities.
- Governance Migration: Implementation of governance requirements, including customer data deletion requests and retention time policies, to meet compliance standards.
- Consumer Shift: Gradual transition of all data consumers to the new AWS environment, with a temporary parallel operation to ensure seamless service.
Solution Architecture
Technology Partner AWS
AWS first: Swisscom chose AWS as its cloud-first provider due to its scalability, enabling seamless expansion of services as demand increases. The advanced tools for analytics, machine learning, and AI offered by AWS help Swisscom innovate and enhance its services, particularly in blue TV and customer experience. Additionally, AWS accelerates Swisscom’s ability to innovate and bring new solutions to the market more quickly.
Voices From the Project
The collaboration with the Swisscom team was characterized by trust and joint focus on the results. Thanks to our expertise in DWH migration and AWS technology, we were able to create a modern, high-performance solution together. In particular, we are pleased to have supported Swisscom laying the foundation for future innovations by migrating the data platform to the cloud.
Lennart Struth
Lennart Struth, Consultant & Data Engineer at b.telligent
b.telligent Services at a Glance
In-depth target architecture design
Collaboratively defining and refining the architectural target solution
Data Migration
Migration path from on-prem DWH to AWS Redshift
AWS Technology Support
Providing ongoing technical assistance and guidance on AWS services and best practices to maximize the benefits of the cloud infrastructure
ETL Migration Tasks
Planning and executing the migration of ETL processes, including data extraction, transformation, and loading, to ensure seamless integration into the new AWS environment
Quality Assurance
End to end testing of the new solution
ML Expertise and Model Creation
Leveraging machine learning expertise to develop and deploy robust ML models tailored to business needs, including model training, evaluation, and optimization
Results & Successes
Successful migration of on-premises TV data warehouse to AWS Redshift with significant cost reduction and less technical complexity
Increasing efficiency and innovation by integrating advanced machine learning models and using AWS cloud capabilities.
Building a scalable infrastructure that serves as the basis for future innovations in analytics.
Success and Benefits of the Migration
The solution delivered significant benefits, including a substantial reduction in external costs related to both infrastructure and personnel. By leveraging AWS Managed Services and Security Services, Swisscom eliminated the need to maintain on-premise software. Technical complexity was reduced, freeing up capacity previously required for operations and development. Additionally, the move to the cloud empowered Swisscom to unlock the full range of cloud capabilities, such as scalability, collaboration, and advanced AI functionalities, driving greater efficiency and innovation.
Key Factors to Success
- Pioneering as one of the first movers in the new AWS region Zürich and within Swisscom
- Exceptional collaboration between b.telligent and Swisscom
- Early involvement of experts with extensive knowledge in DWH migrations and AWS
- Adoption of an agile working style to effectively address challenges as they arise
- Having a pleasant and motivating work environment filled with enjoyment for exploring and experiencing new AWS technologies
The Tech Behind the Success
Amazon Web Services (AWS)
As an Advanced Partner of AWS, b.telligent supports its customers in the migration and setup of data platforms in the AWS cloud. More information here!
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