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Improve Data Quality Through Engineering Rigor And Business Engagement With Synq

Data Engineering Podcast

How does the focus on data assets/data products shift your approach to observability as compared to a table/pipeline centric approach? How does the focus on data assets/data products shift your approach to observability as compared to a table/pipeline centric approach?

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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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Use Consistent And Up To Date Customer Profiles To Power Your Business With Segment Unify

Data Engineering Podcast

However, that's also something we're re-thinking with our warehouse-centric strategy. Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform. You can collect, transform, and route data across your entire stack with its event streaming, ETL, and reverse ETL pipelines.

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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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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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Wizeline and Ascend.io Join Forces to Unleash AI-Powered Data Automation

Ascend.io

” Key Partnership Benefits: Cost Optimization and Efficiency : The collaboration is poised to reduce IT and data management costs significantly, including an up to 68% reduction in data stack spend and the ability to build data pipelines 7.5x Discover how Wizeline’s AI-centric approach can revolutionize your business at wizeline.com.