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Snowflake’s New Python API Empowers Data Engineers to Build Modern Data Pipelines with Ease

Snowflake

This traditional SQL-centric approach often challenged data engineers working in a Python environment, requiring context-switching and limiting the full potential of Python’s rich libraries and frameworks. The post Snowflake’s New Python API Empowers Data Engineers to Build Modern Data Pipelines with Ease appeared first on Snowflake.

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Snowflake Startup Challenge 2024: Announcing the 10 Semi-Finalists

Snowflake

The list of Top 10 semi-finalists is a perfect example: we have use cases for cybersecurity, gen AI, food safety, restaurant chain pricing, quantitative trading analytics, geospatial data, sales pipeline measurement, marketing tech and healthcare. Our sincere thanks go out to everyone who participated in this year’s competition.

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RAG vs Fine Tuning: How to Choose the Right Method

Monte Carlo

It can involve prompt engineering, vector databases like Pinecone , embedding vectors and semantic layers, data modeling, data orchestration, and data pipelines – all tailored for RAG. Like RAG, fine tuning requires building effective data pipelines that can make proprietary data available to the fine tuning process in the first place.

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Data Engineering Weekly #161

Data Engineering Weekly

2) Why High-Quality Data Products Beats Complexity in Building LLM Apps - Ananth Packildurai I will walk through the evolution of model-centric to data-centric AI and how data products and DPLM (Data Product Lifecycle Management) systems are vital for an organization's system.

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Data Engineering Weekly #174

Data Engineering Weekly

The resulting solution was SnowPatrol, an OSS app that alerts on anomalous Snowflake usage, powered by ML Airflow pipelines. link] Adevinta: How we moved from local scripts and spreadsheets shared by email to Data Products Data Product Thinking Shaping the data management to build a reliable, customer-centric data application.

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Pandas 2.0: A Game-Changer for Data Scientists?

Towards Data Science

Although I wasn’t aware of all the hype, the Data-Centric AI Community promptly came to the rescue: The 2.0 There is nothing worst for a data flow than wrong typesets , especially within a data-centric AI paradigm. In the new release, users can rest to sure that their pipelines won’t break if they’re using pandas 2.0,

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Delivering Modern Enterprise Data Engineering with Cloudera Data Engineering on Azure

Cloudera

CDP Data Engineering offers an all-inclusive toolset that enables data pipeline orchestration, automation, advanced monitoring, visual profiling, and a comprehensive management toolset for streamlining ETL processes and making complex data actionable across your analytic teams. . A key aspect of ETL or ELT pipelines is automation.