Remove Data Remove Data Pipeline Remove High Quality Data
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Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Join in with the event for the global data community, Data Council Austin.

Data Lake 262
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Ship Smarter Not Harder With Declarative And Collaborative Data Orchestration On Dagster+

Data Engineering Podcast

Summary A core differentiator of Dagster in the ecosystem of data orchestration is their focus on software defined assets as a means of building declarative workflows. Data lakes are notoriously complex. Your first 30 days are free! Want to see Starburst in action? Can you describe what the focus of Dagster+ is and the story behind it?

Data Lake 162
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Being Data Driven At Stripe With Trino And Iceberg

Data Engineering Podcast

Summary Stripe is a company that relies on data to power their products and business. In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform.

Data Lake 147
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Tackling Real Time Streaming Data With SQL Using RisingWave

Data Engineering Podcast

In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

SQL 173
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Improve Data Quality Through Engineering Rigor And Business Engagement With Synq

Data Engineering Podcast

Petr shares his journey from being an engineer to founding Synq, emphasizing the importance of treating data systems with the same rigor as engineering systems. He discusses the challenges and solutions in data reliability, including the need for transparency and ownership in data systems. Want to see Starburst in action?

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Data Sharing Across Business And Platform Boundaries

Data Engineering Podcast

Summary Sharing data is a simple concept, but complicated to implement well. There are also numerous technical considerations to be made, particularly if the producer and consumer of the data aren't using the same platforms. Dagster offers a new approach to building and running data platforms and data pipelines.

Data Lake 147
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Zenlytic Is Building You A Better Coworker With AI Agents

Data Engineering Podcast

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Data lakes are notoriously complex.

Building 278