It’s all about Data Pipelines. Join Pure Storage Field Solution Architect Chad Hendron and Solutions Director Andrew Silifant for a deep dive into the evolution of data management, focusing on the Data Lakehouse architecture and its role in the age of AI and ML. Our discussion looks at the Data Lakehouse as a powerful combination of a data lake and a data warehouse, solving problems like "data swamps” and proprietary formats of older systems. Viewers will learn about technological advancements, such as object storage and open table formats, that have made this new architecture possible, allowing for greater standardization and multiple tooling functions to access the same data.
Our guests also explore current industry trends, including a look at Dremio's 2025 report showing the rapid adoption of Data Lakehouses, particularly as a replacement for older, inefficient systems like cloud data warehouses and traditional data lakes. Gain insight into the drivers behind this migration, including the exponential growth of unstructured data and the need to control cloud expenditure by being more prescriptive about what data is stored in the cloud versus on-premises. Andrew provides a detailed breakdown of processing architectures and the critical importance of meeting SLAs to avoid costly and frustrating pipeline breaks in regulated industries like banking.
Finally, we provide practical takeaways and a real-world case study. Chad shares a customer success story about replacing a large, complex Hadoop cluster with a streamlined Dremio and Pure Storage solution, highlighting the massive reduction in physical space, power consumption, and management complexity. Both guests emphasize the need for better governance practices to manage cloud spend and risk. Andrew underscores the essential, full-circle role of databases—from the "alpha" of data creation to the "omega" of feature stores and vector databases for modern AI use cases like Retrieval-Augmented Generation (RAG). Tune in to understand how a holistic data strategy, including Pure’s Enterprise Data Cloud, can simplify infrastructure and future-proof your organization for the next wave of data-intensive workloads.
To learn more, visit https://www.purestorage.com/solutions/ai/data-warehouse-streaming-analytics.html
Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts:
https://purecommunity.purestorage.com/
00:00 Intro and Welcome
03:15 Data Lakehouse Primer
08:31 Stat of the Episode on Lakehouse Usage
10:50 Challenges with Data Pipeline access
13:58 Assessing Organization Success with Data Cleaning
16:07 Use Cases for the Data Lakehouse
20:41 Case Study on Data Lakehouse Use Case
24:11 Hot Takes Segment
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It’s all about Data Pipelines. Join Pure Storage Field Solution Architect Chad Hendron and Solutions Director Andrew Silifant for a deep dive into the evolution of data management, focusing on the Data Lakehouse architecture and its role in the age of AI and ML. Our discussion looks at the Data Lakehouse as a powerful combination of a data lake and a data warehouse, solving problems like "data swamps” and proprietary formats of older systems. Viewers will learn about technological advancements, such as object storage and open table formats, that have made this new architecture possible, allowing for greater standardization and multiple tooling functions to access the same data.
Our guests also explore current industry trends, including a look at Dremio's 2025 report showing the rapid adoption of Data Lakehouses, particularly as a replacement for older, inefficient systems like cloud data warehouses and traditional data lakes. Gain insight into the drivers behind this migration, including the exponential growth of unstructured data and the need to control cloud expenditure by being more prescriptive about what data is stored in the cloud versus on-premises. Andrew provides a detailed breakdown of processing architectures and the critical importance of meeting SLAs to avoid costly and frustrating pipeline breaks in regulated industries like banking.
Finally, we provide practical takeaways and a real-world case study. Chad shares a customer success story about replacing a large, complex Hadoop cluster with a streamlined Dremio and Pure Storage solution, highlighting the massive reduction in physical space, power consumption, and management complexity. Both guests emphasize the need for better governance practices to manage cloud spend and risk. Andrew underscores the essential, full-circle role of databases—from the "alpha" of data creation to the "omega" of feature stores and vector databases for modern AI use cases like Retrieval-Augmented Generation (RAG). Tune in to understand how a holistic data strategy, including Pure’s Enterprise Data Cloud, can simplify infrastructure and future-proof your organization for the next wave of data-intensive workloads.
To learn more, visit https://www.purestorage.com/solutions/ai/data-warehouse-streaming-analytics.html
Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts:
https://purecommunity.purestorage.com/
00:00 Intro and Welcome
03:15 Data Lakehouse Primer
08:31 Stat of the Episode on Lakehouse Usage
10:50 Challenges with Data Pipeline access
13:58 Assessing Organization Success with Data Cleaning
16:07 Use Cases for the Data Lakehouse
20:41 Case Study on Data Lakehouse Use Case
24:11 Hot Takes Segment
Databases!!! - Redefining Data Management for Infra & DBA Teams
The Pure Report
42 minutes 5 seconds
2 months ago
Databases!!! - Redefining Data Management for Infra & DBA Teams
The Pure Report welcomes Anthony Nocentino, Sr. Principal Field Solution Architect, to delve into the future of databases and data management. This episode looks at the explosive growth of relational databases and the impact of SQL Server 2025, Oracle 23ai, and AI-driven demands. We explore how Pure Storage is not just keeping pace with database growth but actively simplifying management, scaling, and protection, moving beyond foundational support to offer operational freedom for DBAs and infrastructure teams.
Anthony tackles the pressing challenges faced by database environments today, including fragmented storage infrastructure, manual provisioning, and the complexities of compliance, disaster recovery, and hybrid cloud strategies. Anthony sheds light on how these issues contribute to real-world burnout among DBAs and infra team members. The discussion will also cover the evolving roles of these professionals as they increasingly become platform performance engineers, cloud strategists, and data ops troubleshooters in a world of multiple database engines and unpredictable resource needs driven by AI workloads.
Hear about how Pure's vision for the Enterprise Data Cloud connects to database operations, including key announcements from our Accelerate Vegas and NYC events. We dive into how Pure Fusion with workflow templates and Pure1 offers intelligent, AI-powered workload and resource management, automated policy-based provisioning, and a unified single control plane across on-prem, cloud, and hybrid environments. The episode also explores the implications for enterprise-ready storage with the FlashArray platform family, showcasing how products like FA//XL, FA//X, FA//C, and FA//ST simplify workload expansion and provide significant performance benefits. Finally, we'll get Anthony's "Hot Takes" on critical DBA tasks, dream fixes for database environments, and common myths he'd like to debunk, all while looking forward to Pure's presence at Oracle AI World.
The Pure Report
It’s all about Data Pipelines. Join Pure Storage Field Solution Architect Chad Hendron and Solutions Director Andrew Silifant for a deep dive into the evolution of data management, focusing on the Data Lakehouse architecture and its role in the age of AI and ML. Our discussion looks at the Data Lakehouse as a powerful combination of a data lake and a data warehouse, solving problems like "data swamps” and proprietary formats of older systems. Viewers will learn about technological advancements, such as object storage and open table formats, that have made this new architecture possible, allowing for greater standardization and multiple tooling functions to access the same data.
Our guests also explore current industry trends, including a look at Dremio's 2025 report showing the rapid adoption of Data Lakehouses, particularly as a replacement for older, inefficient systems like cloud data warehouses and traditional data lakes. Gain insight into the drivers behind this migration, including the exponential growth of unstructured data and the need to control cloud expenditure by being more prescriptive about what data is stored in the cloud versus on-premises. Andrew provides a detailed breakdown of processing architectures and the critical importance of meeting SLAs to avoid costly and frustrating pipeline breaks in regulated industries like banking.
Finally, we provide practical takeaways and a real-world case study. Chad shares a customer success story about replacing a large, complex Hadoop cluster with a streamlined Dremio and Pure Storage solution, highlighting the massive reduction in physical space, power consumption, and management complexity. Both guests emphasize the need for better governance practices to manage cloud spend and risk. Andrew underscores the essential, full-circle role of databases—from the "alpha" of data creation to the "omega" of feature stores and vector databases for modern AI use cases like Retrieval-Augmented Generation (RAG). Tune in to understand how a holistic data strategy, including Pure’s Enterprise Data Cloud, can simplify infrastructure and future-proof your organization for the next wave of data-intensive workloads.
To learn more, visit https://www.purestorage.com/solutions/ai/data-warehouse-streaming-analytics.html
Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts:
https://purecommunity.purestorage.com/
00:00 Intro and Welcome
03:15 Data Lakehouse Primer
08:31 Stat of the Episode on Lakehouse Usage
10:50 Challenges with Data Pipeline access
13:58 Assessing Organization Success with Data Cleaning
16:07 Use Cases for the Data Lakehouse
20:41 Case Study on Data Lakehouse Use Case
24:11 Hot Takes Segment
