Two such issues are text-to-SQL query and AI inference ... distinguished AI software engineer at Snowflake, explained to VentureBeat. “The real world use cases often have massive schema ...

Integrating AI output with SQL and providing observability of large language models are ways to put more data analysts in control, according to the data warehousing giant.

Managers of data warehouses of big and small companies realise this sooner or later, that having vast tables of numbers and ...

Snowflake wants to help anyone in the organization interact with structured and unstructured data in natural language, says CEO Sridhar Ramaswamy.

Moreover, SnowConvert AI can help enterprises complete code conversion and testing phases two to three times faster.

“Customers can ask question in natural language and Cortex Analyst translates that into SQL and provides the response.” Using Claude to aggregate and interpret results has enabled Snowflake to ...

With these tables, users can query SQL and do more complex data transformation operations using computing languages, such as python. Nowadays, Snowflake is much more than a data warehouse.

Snowflake Notebooks provide a convenient, easy-to-use development interface for Python, SQL, and Markdown to accelerate development using Snowflake offerings, including Snowflake ML, Streamlit ...