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

Snowflake

Yet while SQL applications have long served as the gateway to access and manage data, Python has become the language of choice for most data teams, creating a disconnect. We’re excited to share more innovations soon, making data even more accessible for all.

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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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5 Takeaways from the Data Pipeline Automation Summit 2023

Ascend.io

Going into the Data Pipeline Automation Summit 2023, we were thrilled to connect with our customers and partners and share the innovations we’ve been working on at Ascend. The summit explored the future of data pipeline automation and the endless possibilities it presents.

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Building a Future in Banking and Capital Markets

The Modern Data Company

And much of this involves finally harnessing data and new technologies to the fullest potential. Many of Deloitte’s Predictions Will Require Access to Real-time Data Analysis The report lists several areas where consumer demand will shift banking products. A robust understanding of potential new customers.

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Snowflake Expands Programmability to Bolster Support for AI/ML and Streaming Pipeline Development

Snowflake

Integrating with APIs and endpoints in a secure way is now possible with external network access, now in private preview. Streamlit gives data scientists and Python developers the ability to quickly turn data and models into interactive, enterprise-ready applications. Check out our ML demo at Summit to see how it works.

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Experts Share the 5 Pillars Transforming Data & AI in 2024

Monte Carlo

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. How fresh is the data? Can I see the pipeline? What is the lineage?