Remove Accessible Remove Cloud Remove Data Governance
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Cloud Data Warehouse Migrations: Success Stories from WHOOP and Nexon

Snowflake

Many of our customers — from Marriott to AT&T — start their journey with the Snowflake AI Data Cloud by migrating their data warehousing workloads to the platform. Today we’re focusing on customers who migrated from a cloud data warehouse to Snowflake and some of the benefits they saw.

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Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera

Data Engineering Podcast

Summary Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor.

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Data Integrity for AI: What’s Old is New Again

Precisely

(Not to mention the crazy stories about Gen AI making up answers without the data to back it up!) Are we allowed to use all the data, or are there copyright or privacy concerns? These are all big questions about the accessibility, quality, and governance of data being used by AI solutions today.

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Where Does Data Governance Fit Into Hybrid Cloud?

Cloudera

At a time when artificial intelligence (AI) and tools like generative AI (GenAI) and large language models (LLMs) have exploded in popularity, getting the most out of organizational data is critical to driving business value and carving out a competitive market advantage. The need for effective data governance itself is not a new phenomenon.

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Scalable Model Development and Production in Snowflake ML

Snowflake

Snowflake ML now also supports the ability to generate and use synthetic data, now in public preview. For image data, running distributed PyTorch on Snowflake ML also with standard settings resulted in over 10x faster processing for a 50,000-image dataset when compared to the same managed Spark solution.

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Accelerate Insight with Proactive Data Governance Practices

Cloudera

More use cases must be deployed to drive more insight and value; more data needs to be made available to more users. Data governance: three steps to success. It is safe to assume that businesses understand the importance of good data governance. Know what data you have. Better governance for better outcomes.

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Why Data Governance Is Crucial for All Enterprise-Level Businesses

Cloudera

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.