The study and extraction of data from exceptionally large data collections are big data. Large amounts of data that expand rapidly with time are often referred to as big data. Because the data is so large and complicated, no standard procedures or data processing tools can adequately handle and store it. There are a plethora of Big Data instances. Firms in numerous sectors create and use data to improve their processes, from social media sites to e-commerce businesses.
Data mining, data analysis, data storage, visualisation, and other operations are all part of big data. If you have undertaken any big data training courses, you would have come across these definitions.
Big Data's Different Types
In big data, there are three categories of data:
Structured
Structured data is the data that could be processed, stored, and retrieved in a specific format. It's well-organised data that can be stored and retrieved from a database quickly and easily, utilising basic techniques. This is the simplest sort of info to handle since you know the data format ahead of time. Structured data is, for instance, the data that a firm saves in its databases in the table format and sheets.
Unstructured
Unstructured data is data that has no recognised form. It's a lot greater than structured information, and it's also a lot more varied. When you do a Google search, the outcomes you obtain are an excellent example of unstructured. You'll get various sizes of websites, movies, photos, text, and other data types.
Semi-structured
As the title indicates, semi-structured info is a mix of unstructured and structured data. It's information that hasn't been categorised into a system but has critical tags that distinguish individual items inside it. A table description in an RDBMS, for example, contains semi-structured info.
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