This is how modern AI databases work with the types of unstructured data mentioned above. Instead of looking for exact matches, these databases look for results that are similar or “close enough.” ...

NEW YORK, Oct. 14, 2024 /PRNewswire/ -- Tarsal, the pioneering force behind advanced security data movement, is proud to announce a major enhancement to its groundbreaking open-source project ...

Get structured with your unstructured data. Early adopters who use big data for business insights are already looking ahead to the next thing it enables – cognitive computing.

SAN FRANCISCO, May 20, 2025--Glean:GO -- Work AI leader Glean today announced a strategic collaboration with Snowflake, the AI Data Cloud company, to simplify and accelerate structured data ...

It involves translating natural language queries into complex SQL queries to filter, join tables and aggregate data.The challenges are further compounded for unstructured data, where by definition ...

This is a significant departure from the traditional ETL world where a single vendor could extract and transform the structured or semi-structured data because the traditional ETL process is a linear ...

Snowflake’s approach is rooted in the idea that AI should operate directly on data where it is stored, instead of requiring ...

Unstructured Data Monitoring lets enterprises extract insights and identify issues from the vast volumes of unstructured data stored in their data warehouses, data lake, and cloud storage locations.

According to McKinsey, businesses have always relied on structured data to drive operations and decision-making, like SKUs, transactions, financial records, and product specifications. Yet, this ...

Conquering the complexities of unstructured data to fuel generative AI (GenAI) apps remains a crucial challenge for many organizations. If said unstructured data can be delivered in clean, canonical ...