What is Structured Data?

Structured data refers to data that is organized in a specific format or schema, such as rows and columns in a table. It is well-defined and follows a specific structure, making it easy to search, query, and analyze. Structured data can be stored in various forms such as relational databases, spreadsheets, and CSV files.

Examples of structured data include:

• Data in a relational database table, with a fixed number of columns and rows.
• Data in a spreadsheet, where each column represents a specific attribute and each row represents a specific record.
• Data in a CSV file, where each line represents a record and the values are separated by a comma.

Structured data can be easily query and analyzed using SQL or other programming languages. It is well suited for use cases such as financial analysis, fraud detection, and customer relationship management.

It is important to note that structured data is different from unstructured data, which has a less organized format, such as text, audio, or video. Unstructured data requires specialized techniques such as natural language processing, computer vision, and speech recognition to extract insights.