An SQL database might hold name, date of birth, address, etc, but analysing unstructured data – via making it semi-structured – can get closer to what consumers think.

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 ...

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.

Essentially, Rockset handles semi-structured data formats such as JSON, Parquet, XML, CSV, and TSV by indexing and storing them in a way that can support relational queries using SQL, as shown in ...

As an example, SQL was the first programming language to return multiple rows per single request. This makes it easier to get data on what is taking place within a set of data—and consequently ...

Organizations have also turned to semi-structured formats to store data. Semi-structured data types include XML, HTML, CSV, and even email, and generally contain tags or other markers (rather than ...