Organizations need to understand the differences between structured and unstructured data. While some data collected by a company is structured, others are not. This means there are differences in how the data is sourced, collected, and scaled. In addition, structured data resides in a different database than unstructured data. How can a company use this information to get the most out of the data it collects?

structured data

Data that can be contained in a fixed field within a file or record falls under the category of structured data. Think of a table and the information it contains. This is structured data. It can be entered, saved, analyzed and queried. Any company that has a database of customer data has structured data. An employee enters the data in a uniform format. The program then organizes them so the company can access and analyze the data. To learn more about structured data, go to this site.

Other examples of structured data include flight reservations, inventory control, and sales transactions. In addition, point-of-sale data and weblog statistics fall into this category. A person often uses SQL to enable querying of this data contained in a relational database.

Unstructured Data

Unstructured data, on the other hand, does not have a fixed format. Computer programs cannot easily use this data because it lacks an easily recognizable structure. This data comes from different sources. As a result, the company must employ specialized tools and data science talent to manage it. Due to the amount of unstructured data being collected today, many data lakes and the Hadoop platform have grown significantly.

According to Realtimecampaign.com, email serves as a type of unstructured data. Presentations, chats, social media posts, and more also fall into this category.

How to tell the difference

A company such as ResoluteAI wants to help users differentiate between structured and unstructured data. A person must know how and where the…