Semi-structured data types include XML, HTML, CSV, and even email, and generally contain tags or other markers (rather than a defined schema) to separate different elements.

Examples of Structured Data: Customer Database: A table in a CRM (customer relationship management) system containing customer names, addresses, email addresses, and phone numbers, all neatly ...

Of course, some structure is present in the metadata that accompanies any file. But with AI/ML processing, additional structured fields of data can be derived from a dataset. So, for example, an ...

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 ...

Data that is defined as unstructured is growing at 55-65 percent each year. Unstructured data can’t be easily stored in a traditional column-row database or spreadsheet like a Microsoft Excel table.