This episode is a re-air of one of our most popular conversations from this year, featuring insights worth revisiting. Thank you for being part of the Data Stack community. Stay up to date with the latest episodes at datastackshow.com.
This week on The Data Stack Show, the crew brings you another conversation live from Data Council in Oakland, California. In this episode, Viktor Kessler from Vakamo explores the evolution of data architecture from rigid warehouses to flexible Lakehouse systems. Powered by Apache Iceberg, this new approach enables seamless data sharing, governance, and potential monetization. Viktor discusses how open-source innovation is transforming data management, highlighting the shift towards treating data as a product and the emerging potential for AI-driven data exchanges. The conversation provides insights into the future of decentralized, adaptable data infrastructure and so much more.
Highlights from this week’s conversation include:
- Viktor's Background and Journey in Data (1:20)
- Evolution of Data Architecture (4:41)
- The Lakehouse Concept (7:12)
- Open Source Innovation (11:05)
- Data Production and Decentralization (15:06)
- Governance in Decentralized Systems (18:53)
- Data Economy and Monetization (21:15)
- Security Concerns in Data Processing (24:21)
- Impact on Data Consumers (27:37)
- Compaction Issues in Data Tables (29:39)
- Open Source Lake Keeper Tool and Parting Thoughts (33:02)
The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
