Mon.Feb 24, 2025

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Enhancing Snowflake Alerts for Dynamic Table Refresh Failures

Cloudyard

Read Time: 2 Minute, 39 Second Snowflake Dynamic Tables offer a powerful way to automate data transformations, ensuring that tables remain fresh and up to date. However, refresh failures can occur due to various reasons such as query errors, or resource constraints. To proactively monitor and respond to such failures, we can leverage Snowflake Alerts to send email notifications whenever a refresh fails.

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Introducing transformWithState in Apache Spark™ Structured Streaming

databricks

Introduction Stateful stream processing refers to processing a continuous stream of events in real-time while maintaining state based on the events seen so far. This.

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AI駆動のセールスアシスタント:生産性の未来

Snowflake

HubSpot 2SnowflakeSnowflake11015 SnowflakeSnowflake800AI SnowflakeCortex AISnowflakeAIApache Iceberg Cortex AILLMStreamlit AI SnowflakeAI Snowflakedocs.snowflake.

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SEC Closes Investigation Into Robinhood Crypto with No Action

Robinhood

Robinhood Announces the SECs Enforcement Division has Closed Its Investigation and Will Not Pursue an Enforcement Action The U.S. Securities and Exchange Commission (SEC) has officially closed its investigation into Robinhood Crypto (RHC). On February 21, 2025, the SECs Enforcement Division advised RHC in a letter that it had concluded its investigation and did not intend to move forward with an enforcement action.

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A Guide to Debugging Apache Airflow® DAGs

In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

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データクリーンルームとは:プライバシー最優先のコラボレーション

Snowflake

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FacetController: How we made infrastructure changes at Lyft simple

Lyft Engineering

Written by Miguel Molina and Arvind Subramanian FacetController If you are curious about Lyfts automatic deployment process on a higher level, please read our blog post on Continuous Deployment. In this post, we will go a little deeper into the deployment stack and how we leverage Kubernetes Custom Resource Definitions (CRDs) to create an abstraction on top of Kubernetes native resources, known at Lyft as facets.

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Securing Data in Striim: Cryptographic Key Management in Striim, Field-Level Encryption, and Vault Integration

Striim

How Striim Keeps Enterprise Grade Streaming Workloads Safe The Streaming Data Security Challenge At Striim our approach to security encompasses protecting data both in motion and at rest, utilizing advanced encryption techniques and integrating with powerful tools. In this blog, Ill walk you through 2 small pieces of this architecture on how Striim secures sensitive data & metadata (a) in motion and (b) at rest.

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Data Clean Rooms Explained: Privacy-First Data Collaboration

Snowflake

If you ask any advertiser about the most disruptive factor in recent years, theyll probably hesitate between two contenders: privacy and AI. While AI is poised to have a transformative impact far beyond advertising in the future, one thing is certain: No organization today can address use cases involving consumer data without prioritizing privacy. Before we dive into the world of data clean rooms, lets take a quick trip back in time to set the stage.

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Web Scraping With Python

WeCloudData

Web scraping is searching and extracting data from web pages over the internet using different scraping tools. The formal definition of web scraping is An automated method used to extract large amounts of data from websites. Python is one of the top choices for web scraping because it has many libraries that can handle complex […] The post Web Scraping With Python appeared first on WeCloudData.

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Generative AI News: Latest Innovations & Breakthroughs

Edureka

In a world where technological advancements are accelerating faster than ever, Generative AI stands at the forefront of innovation, transforming industries and redefining creativity. From revolutionizing content creation to driving breakthroughs in science and business, this powerful technology is reshaping the way we interact with machines. If you want to know about the newest developments, stories, and trends in the field of Generative AI, this blog is the place to go.

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

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Masking in SF Without Hardcoded Roles: Including ARRAY cols

Cloudyard

Read Time: 3 Minute, 37 Second In data-driven enterprises, data security is non-negotiable. Dynamic Masking policies in Snowflake help safeguard sensitive information such as customer emails, payment details, and purchased items. However, a common challenge arises: Hardcoded role names in masking policies make managing access permissions cumbersome.