Gnarly Data Waves

Episode 57

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September 24, 2024

From Hadoop & Hive to Minio & Dremio: Moving Towards a Next Gen Data Architecture

Join this session to learn how Legacy data platforms often struggle with performance, processing, and scaling for robust AI/ML initiatives, particularly in complex multi-cloud environments. The combined power of MinIO and Dremio creates a data lakehouse platform that overcomes these challenges. Learn how this architecture simplifies critical AI tasks, scales seamlessly to meet demands, and streamlines data management for IT teams.

Legacy data platforms often fall short of the performance, processing and scaling requirements for robust AI/ML initiatives. This is especially true in complex multi-cloud (public, private, edge, airgapped) environments. The combined power of MinIO and Dremio creates a data lakehouse platform that overcomes these challenges, delivering scalability, performance and efficiency to ensure successful AI initiatives.

Watch Brenna Buuck, Sr. Technical Evangelist at MinIO and Alex Merced, Sr. Technical Evangelist at Dremio provided insights on:

AI Workflows: How a data lakehouse simplifies critical AI tasks like model training, refinement, feature selection and real-time inference for faster decisions

Scalability and Performance: How a data lakehouse architecture scales seamlessly to meet the fast-growing demands of AI applications

Data Management Efficiency: How a data lakehouse streamlines data management for IT teams, allowing them to focus on innovation

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Case Study

Navigating Decentralized Complexity: How a Large Manufacturer Built a Modern Data Mesh Environment with Dremio

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Quebec Blue Cross Achieves Full CI/CD for Data Analytics with Dremio’s Lakehouse Platform 

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Case Study

Michelin Transforms Data Access and Governance with Dremio’s Open Data Lakehouse Platform 

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