Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is e

How Volkswagen streamlined access to data across multiple data lakes using Amazon DataZone – Part 1

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2024-12-28 21:30:05

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks. A data mesh addresses these issues with four principles: domain-oriented decentralized data ownership and architecture, treating data as a product, providing self-serve data infrastructure as a platform, and implementing federated governance. Data mesh enables organizations to organize around data domains with a focus on delivering data as a product.

In 2019, Volkswagen AG (VW) and Amazon Web Services (AWS) formed a strategic partnership to co-develop the Digital Production Platform (DPP), aiming to enhance production and logistics efficiency by 30 percent while reducing production costs by the same margin. The DPP was developed to streamline access to data from shop-floor devices and manufacturing systems by handling integrations and providing standardized interfaces. However, as applications evolved on the platform, a significant challenge emerged: sharing data across applications stored in multiple isolated data lakes in Amazon Simple Storage Service (Amazon S3) buckets in individual AWS accounts without having to consolidate data into a central data lake. Another challenge is discovering available data stored across multiple data lakes and facilitating a workflow to request data access across business domains within each plant. The current method is largely manual, relying on emails and general communication, which not only increases overhead but also varies from one use case to another in terms of data governance. This blog post introduces Amazon DataZone and explores how VW used it to build their data mesh to enable streamlined data access across multiple data lakes. It focuses on the key aspect of the solution, which was enabling data providers to automatically publish data assets to Amazon DataZone, which served as the central data mesh for enhanced data discoverability. Additionally, the post provides code to guide you through the implementation.

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and third-party sources. Key features of Amazon DataZone include a business data catalog that allows users to search for published data, request access, and start working on data in days instead of weeks. Amazon DataZone projects enable collaboration with teams through data assets and the ability to manage and monitor data assets across projects. It also includes the Amazon DataZone portal, which offers a personalized analytics experience for data assets through a web-based application or API. Lastly, Amazon DataZone governed data sharing ensures that the right data is accessed by the right user for the right purpose with a governed workflow.