Snowflake’s focus on unstructured data is driven by the firm’s plans for agentic AI. That became clearer in February when the ...

Structured data is crucial for training many types of machine learning models, particularly for tasks like classification, regression, and prediction. Integration with Unstructured Data ...

Snowflake Intelligence, launching soon in public preview, allows non-technical users to query and act on structured and ...

Snowflake is addressing the complexity of migrating legacy data systems into the Snowflake ecosystem with SnowConvert AI, a ...

AI chatbots have risen in popularity because they make it easy to find what you are looking for using a simple, ...

Unlike structured data, which fits neatly into rows and columns in a database, unstructured data is ... artificial intelligence (AI) and machine learning models are frequently used to analyze ...

Snowflake wants to reduce enterprises’ reliance on data engineers and data scientists for unstructured data analysis with its ...

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured ... on automation, machine learning (ML), and ...

Snowflake’s 2025 channel goals include increasing the overall percentage of company revenue that comes through the channel ...

Anomalo, the company reinventing enterprise data quality, is adding a major innovation, Workflows, to its second product Unstructured Data Monitoring, introducing a hub for managing and monitoring ...

Anomalo uses machine learning to replace traditional rules-based systems and automatically detect and alert teams about data quality issues across both structured and unstructured data.

Deep learning is a subset of machine learning that uses ... Even though deep learning models can work with data in varying formats, both unstructured and structured, these models are only as ...