Big Data is referred to the collection of data that is huge in volume and is still growing at an exponential rate each second. This data is so large and complex that the traditional data management tools are not able to store or process it in an efficient manner. This is where big data analytics comes into the picture. Big Data could be found in three forms – structured, unstructured, and semi-structured. These types of big data analytics are used to store, access, and process such huge amounts of data. Let us learn more about it: Structured Data
Data that can be stored and processed in the form of fixed-format is termed as 'structured' data. This is the data where the format is well known in advance. With time, computer science is able to develop various techniques that make working with such kind of data and deriving value out of it much easier. Unstructured Data Data that has an unknown form or structure is called unstructured data. Other than being huge in size, there are various other factors that pose multiple challenges when it comes to processing unstructured data. One of the classic examples of unstructured data is a heterogeneous data source that contains a mixture of simple text files, images, and videos. Semi-structured Data As the name suggests, semi-structured data is a combination of both structured and unstructured forms of data. There are two types of semi-structured data, namely XML and JSON (JavaScript Object Notation). Semi-structured data contains tags and elements (known as metadata). These elements are used to group the data and describe how the data is stored. This was an introductory knowledge regarding the various types of big data. However, if you wish to delve deeper, you can enrol in a bachelor’s or masters in big data analytics at a reputed college or university and gain a better knowledge of the subject.
0 Comments
Leave a Reply. |
|