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Serverless Data Pipelines On DataCoral

Data Engineering Podcast

Summary How much time do you spend maintaining your data pipeline? This was a fascinating conversation with someone who has spent his entire career working on simplifying complex data problems. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference.

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Improve Data Quality Through Engineering Rigor And Business Engagement With Synq

Data Engineering Podcast

He highlights the role of data teams in modern organizations and how Synq is empowering them to achieve this. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Can you describe what Synq is and the story behind it?

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Snowflake Startup Challenge 2024: Announcing the 10 Semi-Finalists

Snowflake

The list of Top 10 semi-finalists is a perfect example: we have use cases for cybersecurity, gen AI, food safety, restaurant chain pricing, quantitative trading analytics, geospatial data, sales pipeline measurement, marketing tech and healthcare. Our sincere thanks go out to everyone who participated in this year’s competition.

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Use Consistent And Up To Date Customer Profiles To Power Your Business With Segment Unify

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. What are some of the categories of attributes that need to be managed in a prototypical customer profile?

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End-to-End Data Pipelines: Hitting Home Runs in Data Strategy

Ascend.io

A star-studded baseball team is analogous to an optimized “end-to-end data pipeline” — both require strategy, precision, and skill to achieve success. Just as every play and position in baseball is key to a win, each component of a data pipeline is integral to effective data management.

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Data Pipeline vs. ETL: Which Delivers More Value?

Ascend.io

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

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Bringing Automation To Data Labeling For Machine Learning With Watchful

Data Engineering Podcast

In this episode founder Shayan Mohanty explains how he and his team are bringing software best practices and automation to the world of machine learning data preparation and how it allows data engineers to be involved in the process. Data stacks are becoming more and more complex. That’s where our friends at Ascend.io