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Microsoft Fabric vs. Snowflake: Key Differences You Need to Know

Edureka

It provides real multi-cloud flexibility in its operations on AWS , Azure, and Google Cloud. Additionally, it offers genuine multi-cloud flexibility by integrating easily with AWS, Azure, and GCP. Ideal for: Business-centric workflows involving fabric Snowflake = environments with a lot of developers and data engineers 2.

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Data Engineering Weekly #196

Data Engineering Weekly

The blog emphasizes the importance of starting with a clear client focus to avoid over-engineering and ensure user-centric development. link] CapitalOne: Serverless ML - Lessons from Capital One CapitalOne writes about its experience building Serverless ML on top of AWS Lambda.

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Data Engineering Weekly #203

Data Engineering Weekly

With Astro, you can build, run, and observe your data pipelines in one place, ensuring your mission critical data is delivered on time. This blog captures the current state of Agent adoption, emerging software engineering roles, and the use case category. link] Jack Vanlightly: Table format interoperability, future or fantasy?

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Delivering Modern Enterprise Data Engineering with Cloudera Data Engineering on Azure

Cloudera

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . A key aspect of ETL or ELT pipelines is automation. Resource isolation and centralized GUI-based job management.

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Data Engineering Weekly #214

Data Engineering Weekly

One thing that stands out to me is As AI-driven data workflows increase in scale and become more complex, modern data stack tools such as drag-and-drop ETL solutions are too brittle, expensive, and inefficient for dealing with the higher volume and scale of pipeline and orchestration approaches. We all bet on 2025 being the year of Agents.

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Data Engineering Weekly #182

Data Engineering Weekly

The blog is an excellent summarization of the common patterns emerging in GenAI platforms. link] AWS: Amazon’s Exabyte-Scale Migration from Apache Spark to Ray on Amazon EC2 Amazon’s migration from Apache Spark to Ray is possibly the most fascinating read of recent times. Pipeline breakpoint feature.

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The Race For Data Quality in a Medallion Architecture

DataKitchen

By storing data in its native state in cloud storage solutions such as AWS S3, Google Cloud Storage, or Azure ADLS, the Bronze layer preserves the full fidelity of the data. We have also seen a fourth layer, the Platinum layer , in companies’ proposals that extend the Data pipeline to OneLake and Microsoft Fabric.