Structured data

The success of any business or tech service in today’s digital era greatly depends on data. But this does not mean that every type of data is useful. Only structured data can assist to make quick as well as correct analyses. The reason is clear: it is well organized. Let us explore its exact meaning and importance. 

What is structured data?

The definition of structured data is- it is data that is organized in predefined formats. Generally, it is stored in rows and columns so that machines or computers understand it with ease. The aim of structured data is to simplify searching, analyzing, well as filtering processes. It follows one among many schema types or models. A schema is nothing but a format that defines how rows and columns will be arranged.

How does structured data work?

Structured data organizes all contents in a specific format. This format is defined by the schema. This eventually results in storing as well as processing data hassle-free. For instance, the structured formatting of data helps analytic tools to understand the information easily. In addition to structuring data in rows and columns, tags and labels are also assigned. Thus, eliminating the complexity of database management.

The process of structuring data includes tagging each data point with labels. This way, database management becomes easier.

Structured Data vs. Unstructured Data: Difference

Structured data is well-organized and follows strict formats. On the other hand, unstructured data does not have any specific structure. Also, it may contain images and videos among the data. One more type exists there, i.e., semi-structured data. This includes tags and metadata but does not follow a specific schema. So, there is a difference between structured data and semi-structured data.

Use cases for structured data

Structured data is used in many applications. First, data warehouses use it for managing large datasets. Furthermore, businesses use it for analysis and making key decisions. Not just that, other sectors like finance and retail are heavily reliant on structured data for precise calculations. It also helps search engines like Google and Bing to clearly understand website content. Organizing information becomes an easy gig, which eventually requiring less work to process.

Examples

Hospital patients’ records or bank clients’ records in a CRM are structured data. Storing such data is accompanied by SQL databases. The meaning of the structured data can be easily understood. It typically contains tables with names, prices, and IDs. Providing better services to customers becomes possible with such a format.