We look at how to gain structure from unstructured data, via AI/ML analytics to create new records, selecting object data via SQL and storing unstructured files in NoSQL formats.

There are three classifications of data: structured, semi-structured and unstructured. While structured data was the type used most often in organizations historically, AI and machine learning ...

The ability to access unstructured data directly with SQL syntax is not a new capability for Snowflake but these generative AI-powered functions makes the task easier, said Constellation Research ...

SQL, the Structured Query Language, remains one of the most widely used programming languages, coming in fourth in Stack Overflow’s research for 2023. Just over half (51.52%) of professional ...

“Tabular data” is a broad term that encompasses structured data that generally fits into a specific row and column. It can be an SQL database, a spreadsheet, a .CSV file, etc.

Getting enterprise data into large language models (LLMs) is a critical task for enabling the success of enterprise AI deployments. That’s where retrieval augmented generation (RAG) fits in ...

According to Alluxio, as users and enterprises leverage widely-available analytics engines such as Presto, Apache Spark SQL or Apache Hive, they often run into inefficient data formats and face ...

Wrapping Up SQL Server 2016 introduces some native JSON capabilities so that you can more effectively query stored JSON data as a canonical rowset. This mostly happens when the JSON data is the ...