What is the difference between structured and unstructured information

That has created some issues since unstructured data makes up the vast majority of available data out there on the web, and it only grows larger every year. With more information becoming available on the web, and most of it unstructured, finding ways to use it has become a vital strategy for many businesses. Unstructured data can also be called qualitative data, which basically covers everything that structured data does not.

Unstructured data is also quite diverse, so examples can make up a long list. Some of the most common unstructured data examples include reports, audio files, images, video files, text files, social media comments and opinions, emails, and more.

From the above explanations, the differences between structured and unstructured data should become clear. Structured data is easy to collect, analyze, and store while unstructured data is unorganized and requires more work to properly investigate. Unstructured data also covers a lot more ground than the structured variety, with many more examples that are only growing as the internet continues to expand.

In a sense, unstructured data is similar to how we as humans process and analyze information. If you have a conversation with someone, all the information that is conveyed is done so in an unorganized fashion.

It can be human- or machine-generated. Common examples of machine-generated structured data are weblog statistics and point of sale data, such as barcodes and quantity. Plus, anyone who deals with data knows about spreadsheets: a classic example of human-generated structured data.

Unstructured data is data stored in its native format and not processed until it is used , which is known as schema-on-read. It comes in a myriad of file formats, including email, social media posts, presentations, chats, IoT sensor data, and satellite imagery.

As there are pros and cons of structured data, unstructured data also has strengths and weaknesses for specific business needs. Some of its benefits include:. There are also cons to using unstructured data.

It requires specific expertise and specialized tools in order to be used to its fullest potential. Unstructured data is qualitative rather than quantitative, which means that it is more characteristic and categorical in nature. There are types of data- structured semi-structured and unstructured data.

In this article, we have brought you the types of data- structured vs unstructured and have discussed the differences they have. So stay tuned to keep knowing what is structured data and unstructured data —. Structured data is quite a familiar term to find. And in this article, you will know the meaning of it.

Structured data types can be simplified into easy words by referring to it as data which can help in describing your site. The search engines must get know the description of your site. And hence, you would require to present the description in a language that the search engine can understand. The code is put to use by the search engines. They use it to help you gain views. They present your site in a much richer way.

And putting this piece of content on your site is much helpful because of the obvious reasons mentioned before. And if you give structured data in your site, then using that, your site can be presented by the search engine in a much attractive way than it would look otherwise. Hence, structured data is a medium through which your site talks to the search engine.

You let the search engine know the contents you offer. And later on, the search engine decides to show it in the search results to get people relevant search results. And it can more assertively be said, that search engines help the site gaining views and being notified if the site has structured data. Therefore, the benefits of having structured data are many. In this part, we would reveal you what is unstructured data.

Unstructured data definition is the data that has no specific model or structure that is uniquely identifiable. Hence, it cannot be used by search engines easily. It can rather be known as data that is not well-organized. Typical examples of structured data are names, addresses, credit card numbers, geolocation, and so on.

Unstructured data is more or less all the data that is not structured. Even though unstructured data may have a native, internal structure, it's not structured in a predefined way.

There is no data model; the data is stored in its native format. Typical examples of unstructured data are rich media, text, social media activity, surveillance imagery, and so on. The amount of unstructured data is much larger than that of structured data. This means that companies not taking unstructured data into account are missing out on a lot of valuable business intelligence.

Enjoying This Article? Receive great content weekly with the Xplenty Newsletter! Integrate Your Data Today! Try Xplenty free for 7 days. No credit card required. Get Started. Semistructured data is a third category that falls somewhere between the other two. It's a type of structured data that does not fit into the formal structure of a relational database. But while not matching the description of structured data entirely, it still employs tagging systems or other markers, separating different elements and enabling search.