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Seamless SQL And Python Transformations For Data Engineers And Analysts With SQLMesh

Data Engineering Podcast

Summary Data transformation is a key activity for all of the organizational roles that interact with data. Because of its importance and outsized impact on what is possible for downstream data consumers it is critical that everyone is able to collaborate seamlessly. Can you describe what SQLMesh is and the story behind it?

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Use Your Data Warehouse To Power Your Product Analytics With NetSpring

Data Engineering Podcast

NetSpring is a warehouse-native product analytics service that allows you to gain powerful insights into your customers and their needs by combining your event streams with the rest of your business data. Visit: dataengineeringpodcast.com/data-council today! Don't miss out on their only event this year!

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Data Engineering Weekly #173

Data Engineering Weekly

link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. seconds, enhancing real-time sports data analytics efficiency!

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Data Warehouses Vs Operational Data Stores Vs Data Lakes – How To Store Your Data For Analytics

Seattle Data Guy

A few months ago, I uploaded a video where I discussed data warehouses, data lakes, and transactional databases. However, the world of data management is evolving rapidly, especially with the resurgence of AI and machine learning.

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Reflecting On The Past 6 Years Of Data Engineering

Data Engineering Podcast

In that time there have been a number of generational shifts in how data engineering is done. Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Materialize]([link] Looking for the simplest way to get the freshest data possible to your teams?

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Composable data management at Meta

Engineering at Meta

In recent years, Meta’s data management systems have evolved into a composable architecture that creates interoperability, promotes reusability, and improves engineering efficiency. Data is at the core of every product and service at Meta. Data is at the core of every product and service at Meta.

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Reduce The Overhead In Your Pipelines With Agile Data Engine's DataOps Service

Data Engineering Podcast

Summary A significant portion of the time spent by data engineering teams is on managing the workflows and operations of their pipelines. Agile Data Engine is a platform designed to handle the infrastructure side of the DataOps equation, as well as providing the insights that you need to manage the human side of the workflow.