Swiss customers build their modern data strategy on AWS

In today’s data-driven world, organizations around Switzerland are leveraging AWS to build their modern data strategies. Companies like Roche and Simpego use AWS to develop analytics, data-centric applications, and AI solutions.

AWS offers a comprehensive set of data capabilities that enable companies to make better, faster decisions, leverage generative AI, and optimize their business.

In this blog post, you’ll discover how these two Swiss customers are leveraging AWS to build their modern data strategies, taking advantage of AWS flexibility, scalability, and advanced data services.

Roche: enabling enterprise-wide analytics and AI with automated compliance

As a leading pharmaceutical company, Roche needed a cloud architecture that could serve the needs of data scientists looking for fast, easy access to services and data, while also addressing compliance requirements around risk control and data governance.

Roche identified the need to decouple the long-term storage of data from the ephemeral services and compute resources used to process and consume that data. This crystalized into a centralized “data hub” built on AWS using services like Amazon Redshift, Amazon S3, and AWS Lake Formation. This data hub acts as a distributed, highly secured data store with rigorous metadata capture and onboarding processes. Data is logically separated from compute, with the data hub providing permanent, tightly controlled storage.

For processing and analysis, Roche uses AWS environments provisioned via AWS Service Catalog and AWS CloudFormation as temporary “bubbles.” These isolated environments allow data scientists to quickly access AWS services like Amazon SageMaker while enforcing policies like encryption and network security.

When a data scientist needs data, they use a custom user interface to browse the cataloged datasets. When they identify a dataset they are interested in, they request access. Approved requests result in cross-account sharing of the dataset to the bubble environment in read-only mode, so no data movement is required.

Through this architecture, Roche has achieved three key outcomes:

1. Data governance – Centralized metadata, onboarding processes, and access controls enable Roche to rigorously track and manage data usage while maintaining compliance.
2. Flexibility for data scientists – The provisioned bubbles give data scientists a self-service way to quickly access AWS tools and approved data sources without compromising security.
3. Automation – By leveraging Service Catalog and CloudFormation, Roche can automate environment creation and policy enforcement, increasing efficiency and consistency.

In summary, Roche’s architecture balances the needs of data scientists and compliance teams through purposeful separation of concerns, robust data governance processes, and strategic automation enabled by AWS services.

Learn more about Roche compliant data architecture in this video:

Simpego: from clickstreams to insights in minutes

Simpego is a modern Swiss insurer, and one of the fastest-growing startups in the industry. Founded in 2016 and fully cloud-native, it offers insurance solutions for cars, motorbikes, buildings, pets, and more.

Simpego needed a highly scalable and cost-effective solution to process large volumes of customer data, automate business processes, and leverage AI for pricing optimization.

To address this need, Simpego built their core business architecture on AWS, leveraging a range of data and analytics services. Their architecture includes an Amazon EKS cluster that ingests customer data from various channels, which is then streamed into an Amazon S3 data lake using Amazon Kinesis Firehose. AWS Glue performs data transformations and loads the processed data back into S3, enabling analysis with Amazon Athena. This data feeds into Simpego’s process automation engine, which handles contract management, customer communications, and triggers various data streams. Additionally, Simpego incorporates AI models for pricing optimization and generating insights from their data.

By running their data-driven processes on AWS, Simpego benefits from scalable and cost-effective infrastructure, seamless integration of various data services, and the ability to leverage advanced AI capabilities. This enables Simpego to provide highly competitive and personalized insurance products to their customers while maintaining agility and driving innovation in the insurance industry.

Learn more about Simpego use case and their data architecture in this video:

Conclusions

In this blog post, you have learned how two Swiss companies – Roche and Simpego – are leveraging AWS to build their modern data strategies. From enterprise-wide analytics with automated compliance to AI-driven pricing optimization, these customers are leveraging the flexibility and scalability of AWS data services to drive innovation and optimize their businesses.

To explore more customer success stories and learn how AWS empowers organizations in Switzerland with their data strategies, visit our AWS in Switzerland and customers success stories pages.