Thu.Oct 31, 2024

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Testing DuckDB’s Large Than Memory Processing Capabilities.

Confessions of a Data Guy

I am a glutton for punishment, a harbinger of tidings, a storm crow, a prophet of the data land, my sole purpose is to plumb the depths of the tools we use every day in Data Engineering. I find the good, the bad, the ugly, and splay them out before you, string ’em up and […] The post Testing DuckDB’s Large Than Memory Processing Capabilities. appeared first on Confessions of a Data Guy.

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How to Fine-Tune T5 for Question Answering Tasks with Hugging Face Transformers

KDnuggets

Fine-tuning the T5 model for question answering tasks is simple with Hugging Face Transformers: provide the model with questions and context, and it will learn to generate the correct answers.

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New Snowflake Deployment: Mexico and South Korea Coming Soon

Snowflake

Snowflake is excited to announce a significant expansion of our AI Data Cloud infrastructure with support for Microsoft Azure Mexico by the end of Snowflake’s fiscal year, and support for Microsoft Azure in Seoul in the first half of 2025. These deployments underscore Snowflake’s continued commitment to providing our customers with a unified and secure experience, regardless of where their data resides.

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When to Go Out and When to Stay In: RAG vs. Fine-tuning

KDnuggets

This article presents a comprehensive discussion of when to choose which approach for your LLM and potential hybrid solutions.

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Apache Airflow® Best Practices for ETL and ELT Pipelines

Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.

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Modern Data Architecture: Data Mesh and Data Fabric 101

Precisely

Key Takeaways: Data mesh is a decentralized approach to data management, designed to shift creation and ownership of data products to domain-specific teams. Data fabric is a unified approach to data management, creating a consistent way to manage, access, and share data across distributed environments. Both approaches empower your organization to be more agile, data-driven, and responsive so you can make informed decisions in real time.

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Win the CSP & MSP Markets by Leveraging Confluent’s Data Streaming Platform and OEM Program

Confluent

Deploying Confluent Platform in conjunction with Confluent's OEM Program can help CSPs and MSPs develop high-margins, while maintaining operational excellence and lowering risk.

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The Complete Guide to Data Uniqueness

Monte Carlo

Remember the Healthcare.gov launch fiasco? Millions of Americans tried to sign up for health insurance—and couldn’t. The site crashed under heavy demand and even when people did manage to enroll, the system sometimes created multiple insurance plans for the same person. Behind this chaos was an often-overlooked but critical aspect of data management: data uniqueness.

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Enabling Seamless Cloud Migration and Real-Time Data Integration for a Nonprofit Educational Healthcare Organization with Striim

Striim

A nonprofit educational healthcare organization is faced with the challenge of modernizing its critical systems while ensuring uninterrupted access to essential services. With Striim’s real-time data integration solution, the institution successfully transitioned to a cloud infrastructure, maintaining seamless operations and paving the way for future advancements.

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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

The rise of AI and GenAI has brought about the rise of new questions in the data ecosystem – and new roles. One job that has become increasingly popular across enterprise data teams is the role of the AI data engineer. Demand for AI data engineers has grown rapidly in data-driven organizations. But what does an AI data engineer do? What are they responsible for?