Structured Vs. Semi-Structured Vs. Unstructured Data: Know the Difference Between Structured, Semi-structured, and Unstructured Data
All three of them are variations of the structures present in big data, and they serve a similar purpose. But there is a significant difference between structured, semi-structured, and unstructured data. In this article, we will discuss the same in a tabular form. But before we get into that, let us first understand more about Big Data.
Big data refers to something that deals with a huge volume of information or data and its overall execution. This data can be of various extensive types and of a very high velocity. Since the amount of data is pretty large, Big data has three broad categories based on how they organize the contained information. These three types are Unstructured, Semi-Structured, and Structured data. Let us know a bit more about each of these.
What is Structured Data?
This type of data consists of various addressable elements to encourage effective analysis. The structured form of data gets organized into a repository (formatted) that acts as a typical database. Structured data works with all kinds of data that one can store in the SQL database in a table that consists of columns and rows. These consist of relational keys, and one can easily map them into pre-designed fields. People mostly use and process structured data for managing data in the simplest form during the development process. Relational data is one of the most commendable examples of Structured Data.
What is Semi-Structured Data?
It is the type of information and data that does not get stored in a relational type of database but has organizational properties that facilitate an easier analysis. In other words, it is not as organized as the structured data but still has a better organization than the unstructured data. One can use some processes for storing this type of data and info in the relational database, and this process can be pretty difficult for some semi-structured data. But overall, they ease the space available for the contained information. XML data is an example of semi-structured data.
What is Unstructured Data?
It is a type of data structure that does not exist in a predefined organized manner. In other words, it does not consist of any predefined data model. As a result, the unstructured data is not at all fit for the relational database used mainstream. Thus, we have alternate platforms to store and manage unstructured data. It is pretty common in IT systems. Various organizations use unstructured data for various business intelligence apps and analytics. A few examples of the unstructured data structure are Text, PDF, Media logs, Word, etc.
Difference Between Structured, Semi-structured, and Unstructured Data
| Parameters | Structured Data | Semi-Structured Data | Unstructured Data |
| Data Structure | The information and data have a predefined organization. | The contained data and information have organizational properties- but are different from predefined structured data. | There is no predefined organization for the available data and information in the system or database. |
| Technology Used | Structured Data words on the basis of relational database tables. | Semi-Structured Data works on the basis of Relational Data Framework (RDF) or XML. | Unstructured data works on the basis of binary data and the available characters. |
| Flexibility | The data depends a lot on the schema. Thus, there is less flexibility. | The data is comparatively less flexible than unstructured data but way more flexible than the structured data. | Schema is totally absent. Thus, it is the most flexible of all. |
| Management of Transaction | It has a mature type of transaction. Also, there are various techniques of concurrency. | It adapts the transaction from DBMS. It is not of mature type. | It consists of no management of transaction or concurrency. |
| Management of Version | It is possible to version over tables, rows, and tuples. | It is possible to version over graphs or tuples. | It is possible to version the data as a whole. |
| Robustness | Structured data is very robust in nature. | Semi-Structured Data is a fairly new technology. Thus, it is not very robust in nature. | – |
| Scalability | Scaling a database schema is very difficult. Thus, a structured database offers lower scalability. | Scaling a Semi-Structured type of data is comparatively much more feasible. | An unstructured data type is the most scalable in nature. |
| Performance of Query | A structured type of query makes complex joining possible. | Semi-structured queries over various nodes (anonymous) are most definitely possible. | Unstructured data only allows textual types of queries. |
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