Structured and unstructured data in big data?
Structured and unstructured data is the lifeblood of a business, as it means the collection of information and this information comes in a huge variety of formats? from the relational database to your last tweet on Twitter or your last post on Facebook.
All of that data, in all different formats, can be arranged in one of two categories? Read more about: Structured and unstructured data.
Structured data and unstructured data are types of big data. Big data means a large amount of data which is difficult to collect, store, maintain, analyze and visualize. There are three types of big data, namely:
Here we will discuss structured data and unstructured data.
Structured data is any data which is highly organized with definite length and format, ?schema? (structural representation of what is in the data). Structured data can be easily retrieved.
It is stored in the database, excel sheet, or in CSV file (Comma Separated Values) having a fixed number of rows and columns with well-defined attributes. Structured data is simple to handle and easy to understand, store, format, execute, process, and analyze.
Structured data is generally managed by SQL (Structured Query Language) for analyzing, managing and querying the data stored in Relational Data Base Management System and Spreadsheets.
Merits of structured data
- It can be easily handled by machine learning algorithms.
- It can be easily accessed and used by business users.
- There is increased access to more tools for using and analyzing structured data.
Demerits of Structured and unstructured data
- There are limited storage options.
- A predefined purpose limits the use of structured data.
Example of Structured and unstructured data
Under the attribute email id, all email ids are mentioned and under the attribute phone number all phone numbers are mentioned, it is kind of an employee table. In structured data, there is no need to put much effort as things are presented in an organized manner.
Unstructured data is in its native format, which means it is not in a structured format and it is not processed until it is used. Due to the lack of any format, it becomes difficult and time-consuming to process and analyze unstructured data.
Unstructured data is human-generated and machine-generated. Human-generated data is available in a huge amount across the internet, for example, picture uploaded on Facebook. Machine-generate data scientific data gained from various experiments, satellite images, etc.
Merits of Unstructured data
- It can be stored in its native format.
- It can be accumulated quickly and easily.
- It is often stored in cloud data lakes for massive storage.
Demerits of Unstructured data
- It requires specialized tools to manipulate.
- It requires data science expertise.
Example of unstructured data
Structured and unstructured data include text, audio, video, satellite imagery, surveillance video recording, etc.