Last Updated on by Kumar Raja

Understanding Different Data Types In Data Science

The prominence of Big Data & Data Science is overgrowing in the industries of all types across every major sector. Enterprises these days are taking a competitive edge over their competitors by making accurate data-driven smart decisions. Insights from Big Data aren’t just helping the enterprises to stay competitive but are also helping them to take revolutionary steps forward. Get a clear idea of the data analysis technique in Data Science by joining for the advanced Data Science Training In Hyderabad program offered by Kelly Technologies.

Now, let’s take a look at the different Data types in Data Science.

Types Of Data-

Data can be broadly classified into three different categories, namely structured data, semi-structured data & unstructured data.

Structured Data-

Structured data can be interpreted as a predesigned data that can be collected & directly stored in an organized way. As the flow of information in this format of data remains well organized, we can easily retrieve the information & analyze it without much difficulty. Usually, data of this format gets deposited into a repository & can be used for specific purposes.

Compared to any other data type, Data Scientists will be finding it easy to explore the insights & make a conclusion based on the structured data type. However, as per the experts’ view, this format of data is found very less in percentage compared to the other data types. Also, storing this type of data is very easy.

Unstructured Data-

This is a data type in which data doesn’t have any specific format & there’s no predefined way to store this type of data.  Since this data type has no specific format, storing it inside the relational database is quite difficult. We can make use of different tools to explore the insights from an unstructured data type & it consumes a considerable amount of time. There are different techniques like batch processing, real-time processing, distributed Processing & other suitable approaches that help in processing this type of data. 

Semi-Structured Data-

This type of data has semantic tags; however, they don’t specifically coordinate with the relational database conventional structures. These data types have different attributes though they belong to the same class.

Get to know about the data modeling process for different data types by working on projects in real-time by joining for the advanced Data Science training program offered by Kelly Technologies.

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