Mon.Mar 31, 2025

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Best Automation Tools In 2025 for Data Pipelines, Integrations, and More

Seattle Data Guy

Since I started working in tech, one goal that kept coming up was workflow automation. Whether automating a report or setting up retraining pipelines for machine learning models, the idea was always the same: do less manual work and get more consistent results. But automation isnt just for analytics. RevOps teams want to streamline processes… Read more The post Best Automation Tools In 2025 for Data Pipelines, Integrations, and More appeared first on Seattle Data Guy.

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Scalable Model Development and Production in Snowflake ML

Snowflake

Despite the best efforts of many ML teams, most models still never make it to production due to disparate tooling, which often leads to fragmented data and ML pipelines and complex infrastructure management. Snowflake has continuously focused on making it easier and faster for customers to bring advanced models into production. In 2024, we launched over 200 AI features, including a full suite of end-to-end ML features in Snowflake ML , our integrated set of capabilities for machine learning mode

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Announcing Automatic Publishing to Power BI

databricks

Were excited to announce the Public Preview of the Microsoft Power BI task type in Databricks Workflows, available on Azure, AWS, and GCP. With this.

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VIP Cheatsheet: Transformers & Large Language Models

KDnuggets

Learn more about this handy resource created by Afshine and Shervine Amidi for Stanford's CME 295 course.

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The Ultimate Guide to Apache Airflow DAGS

With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you

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How Willis Towers Watson Transformed Work & Rewards with Data Intelligence Powered by Unity Catalog

databricks

Willis Towers Watson (WTW) is a multinational company that provides a wide range of services in commercial insurance brokerage, risk management, employee benefits, and actuarial.

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Mobile GraphQL at Meta in 2025

Engineering at Meta

Mobile GraphQL is a framework used at Meta for fetching data in mobile applications using GraphQL , a strongly-typed, declarative query language. At Meta it handles data fetching for apps like Facebook and Instagram. Sabrina, a software engineer on Metas Mobile GraphQL Platform Team, joins Pascal Hartig on the Meta Tech podcast to discuss the evolution and future of GraphQL.

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Monitoring Unstructured Data with Monte Carlo

Monte Carlo

The idea of leveraging unstructured data in production isnt new by any means but in the age of AI, unstructured data has taken on a whole new role. Ubiquitous access to models that can easily extract insight and information from text, images, and videos has opened the door for organizations to take advantage of datasets that were previously ignored.

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Accelerating SQL Server Data Replication with SQL2Fabric-X

Striim

Striim augments SQL2Fabric Mirroring to additionally replicate real-time data to Azure Databricks and Microsoft Fabric Data Warehouse For years, SQL Server has been a cornerstone for enterprise data management, but moving that data in real time to modern cloud platforms has often been complex, slow, and operationally intrusive. But real-time data movement for replication, mirroring, or analytics shouldnt be a bottleneckit should be an enabler.

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Globalizing Productions with Netflix’s Media Production Suite

Netflix Tech

Jesse Korosi , Thijs van de Kamp , Mayra Vega , Laura Futuro , Anton Margoline The journey from script to screen is full of challenges in the ever-evolving world of film and television. The industry has always innovated, and over the last decade, it started moving towards cloud-based workflows. However, unlocking cloud innovation and all its benefits on a global scale has proven to be difficult.

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