Why we need to Structure Data | Classification of Big Data

Why we need to Structure Data | Classification of Big Data

Structured Data is a kinda Classification of data based on its nature and Structure, Let's see why this type of data is important in most organizations, and what are the benefits of having such kinda information.

Why do we need Data?

                It's an important thing to note that in the 21'st century information is the most powerful weapon. This information can be of any kind whether it is personal information or organization information or confidential information, Everything is important. It tells about the characteristics of a person or an organization or government. For example, if we have the personal information of someone we can do a social engineering attack and get required things like money or anything else.

                Every day huge terra-bytes of data are generated from different resources like search engines, social media apps, videos, audio, and even from this article. So To understand the data and process it, we need to first arrange the data in proper structure so we can input it to some program or computer. This is where the classification of data comes into the picture. Big data deals with a huge amount of information for finding a particular trait, pattern, or predicting the future to achieve this we need to arrange the data and classify it.

Structured Data :

                If you have learned about DBMS you might be known about schema which is saving data in predefined tables of different attributes or features. Structured data has additional features which we will be looking further in the article. Most organizations thrive to achieve this type of data or to covert their current information/data into this. Data is stored in a Proper way like rows and columns common example of this is RDBMS.

Semi-Structured Data : 

                Semi-Structured data is also a type of data classification in which it has inconsistent structure but it is self-describing. For example, if you make a form to fill in the personal details of a few members then it will be an example of semi-structured data as most of the members might not fill in all the required information and some might fill in wrong data, but we can say that all the data is corresponding to personal information. It is stored in the form of markup languages like XML, JSON, etc. This does not have any specific rules or structure but we can get a broader view of the information by seeing the data.

Unstructured Data :

                Any Data which is not arranged in predefined format or Schema is known as unstructured data. Most of the Organization data is in this form around 80-90%. The sources of the information mostly generate unstructured data and there needs to be some way or methodology to convert this form into structured, information like audio, video, chat messages, social media data, emails, word documents. PowerPoint presentations, web pages all come under this category.

What are the Advantages of Structured Data?

                When Information is stored in a predefined manner or in a schema there are several advantages for both computational and memory efficiency. The major advantage is that computers or programs can easily understand this data and interpret it. 
  • CRUD Operations: When we want to do operations like Insert Update Delete and Viewing data this can be easily done a Structured data as they can be accessed using different indexes or with primary keys in case of RDMS storage. DML or data manipulation Language can be easily used to operate on them.
  • Scalability and Security: We can add or remove data from the storage based on our needs, In other words, it is fully scalable to any scale. If all the data is stored in a predefined manner then it is easy to apply encryption methods to secure the data which enables the security of the information.
  • Indexing and Accessibility: Retrieving required information from big data is a very tedious task as it needs to know what information is useful and what is not, with the help of indexing we can achieve this goal easily, and accessing the data is more fast and efficient.
  • Processing: Processing can be any kind of processing like Accessing data, inputting data to a program like ML algorithm, etc. Structured data support all the ACID features which are, Atomicity, Consistency, Isolation, and Durability.

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