Snowflake has announced a definitive agreement to acquire Select Star, a San Francisco-based startup specializing in context metadata platforms. This move aims to bolster Snowflake’s Horizon Catalog, a comprehensive suite for data discovery, management, and governance within its Data Cloud ecosystem. Enhancing Data Discovery and Governance Horizon Catalog serves as a unified platform that helps
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All posts tagged in Data Science
Many teams working with machine learning (ML) and data face a sneaky problem: annotation mistakes. These errors can slow down progress and make the whole process more expensive. Recent studies show that annotation errors are more common than many realize. For example, Apple’s research found about 10% error rates in search relevance tasks. Even the
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When managing millions of documents, slow systems and rising costs can be a real headache. A common mistake is treating metadata and content as one big chunk of data. But separating them can make a huge difference. By thinking of metadata as a high-speed, small-data workload and content as a large, less frequent task, a
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Many people think the main challenge in enterprise AI is the technology itself. But a recent IBM study shows that the real problem is often hidden deep within the organization — data silos. These silos are isolated pools of data that don’t communicate with each other, making it hard to use data effectively across different
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Starburst, known for its data platform that helps apps and AI work better, has teamed up with Snowflake, the company behind the AI Data Cloud. Their goal is to improve how data is shared and understood across different tools and platforms. This partnership focuses on creating open standards so that companies can work with data
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Many organizations today are focusing heavily on upgrading their databases to support new technologies and applications. The push for modernization is driven by the need for faster, more reliable, and scalable systems that can handle the demands of modern software, including artificial intelligence. A recent report from Yugabyte, experts in distributed databases, highlights the key
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Artificial intelligence is changing the way architecture, engineering, and construction (AEC) teams handle their project data. A company called Tektome has introduced a new tool that makes working with past project information easier and smarter. This tool turns scattered documents and drawings into a centralized, searchable database that saves time and boosts productivity. Introducing KnowledgeBuilder:
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Google has introduced a new visual query builder within its Log Analytics tool to make analyzing cloud logs easier for everyone. This tool is designed for developers, DevOps teams, and site reliability engineers (SREs) who need to dig into cloud workload data but might not be SQL experts. It helps turn complex log data into
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Many big companies jumped on the data mesh bandwagon, hoping it would fix the problems of traditional data lakes. Initially, it looked promising. Companies like Netflix and Intuit adopted this approach, expecting smoother data workflows and better quality. But just a few years later, the enthusiasm faded. Some now say data mesh was just a
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Not many developers today realize just how much easier their lives are thanks to REST and JSON. Before these standards became widespread, sharing data and code over a network was a complicated mess. Developers had to deal with clunky protocols, brittle integrations, and lots of headaches. It’s easy to forget how rough things used to
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