Data Mesh Architecture at Large Enterprises (w/ Moritz Heimpel and Ben Flusberg)
Dec 8, 2023
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Moritz Heimpel from Siemens and Ben Flusberg from Cox Automotive discuss their experiences adopting a data mesh architecture and collaborating with data at scale in large organizations. They explore topics such as setting up infrastructure to scale, domain specific ownership of data, data security, and the future of the data industry.
Implementing a data mesh architecture fosters collaboration at scale while ensuring data quality and security.
Clear policies, documentation, and metadata catalogs are essential for facilitating data sharing and compliance with regulations.
Deep dives
Data ownership and strategies at Siemens and Cox Automotive
Moritz Hemphold and Ben Flusberg discuss their roles as data stewards in large organizations, focusing on the differences in data needs between complex organizations and smaller ones. They highlight the importance of centralizing certain aspects of data management while maintaining a federated approach for other areas. Data mesh frameworks and processes are implemented to foster collaboration at scale while ensuring data quality and security. The role of incentives and culture in promoting data sharing and collaboration is emphasized, with specific examples of chargeback models and marketplace implementations.
Challenges and considerations in data ownership
The episode delves into the challenges and considerations surrounding data ownership, highlighting the need for clear delineation of responsibilities and decision-making regarding data products. The importance of striking a balance between centralization and decentralization is emphasized, with a focus on optimizing efficiency and collaboration. The speakers also discuss the significance of cultural shifts and incentives in promoting data sharing and collaboration, while ensuring compliance with legal and security requirements.
Data sharing, security, and data contracts
The podcast explores the intricacies of data sharing, data security, and establishing data contracts within large organizations. The speakers describe three levels of data shareability, ranging from highly restricted to not limited, and the challenges of implementing and maintaining these access levels. They emphasize the importance of clear policies, documentation, and metadata catalogs to facilitate data sharing and ensure compliance with legal and privacy regulations. Furthermore, they discuss the considerations and processes for evaluating data sensitivity and rights to access, including audits and frequent reassessments.
Looking towards the future of the data industry
In the final segment, the speakers share their hopes for the future of the data industry. They express a desire for greater democratization of data, making it more accessible and easier to use. Additionally, they envision increased data literacy throughout organizations, with individuals having a deeper understanding of data and its interpretation for decision-making. They also highlight the importance of ethical AI, emphasizing the need for frameworks and practices to address biases, disinformation, and other ethical concerns in the evolving landscape of artificial intelligence.
Moritz Heimpel from Siemens and Ben Flusberg from Cox Automotive have very similar jobs. They both act as stewards of the data strategies at large, complex companies.
In this episode, we get into what it’s like to collaborate with data at scale. Ben and Mortitz share their experiences adopting a data mesh architecture and what that looks like at their organizations.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.
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