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Print Posted By Tech Directory on 08/28/2017

What is Big Data?

What is Big Data?

Big data refers to data sets that are either too complex or too large that traditional data processing application software cannot deal with it adequately. Today, “big data” is increasingly being used in the context of predictive analytics and user behaviour analytics among other advanced data analytics methods used to extract value from data. The usage is no longer limited to the size of the data set in question. 

Characteristics of Big Data

a) Volume

One of the distinguishing characteristics of big data is its huge volume. To this extent, the size of data is a key factor that determines whether it can properly be referred to as big data or not. 

b) Variety

Variety relates to heterogeneous sources of data. Some time back, databases and spreadsheets were the only sources of data considered by most applications. Today, applications are analyzing data in the form of photos, emails, videos, PDfs, monitoring devices, and audio, among others. 

c) Velocity

Velocity refers to the speed at which data is generated and flows in from sources such as business processes, sensors, application logs, social media sites and networks and mobile devices. The speed at which data is generated and processed to meet the demand determines its real potential.

d) Variability

Variability deals with the inconsistency that characterizes big data so that it becomes difficult to handle and manage effectively.

Categories of big data

a) Structured big data

Structured big data is that which can be stored, accessed and processed in a fixed format which is well known in advance. Computer scientists have developed techniques of working with structured big data and deriving value from it. However, the growth of structured data to the tune of multiple zettabytes poses challenges in storage and processing. An employee table in a database is a perfect example of structured big data.

b) Unstructured big data

Unstructured data does not have a known form or structure. It poses great challenges in processing to derive value from it. Therefore, an organization may have volumes of unstructured data but find it difficult to derive value from it. An example of unstructured data is the output returned by a “Google search.” 

c) Semi-structured big data

Semi-structured data contains both the characteristics of structured and unstructured data to some extent. An example of semi-structured data is data stored in an XML file. 

Advantages of big data

  • Application of big data enables organisations to utilize outside intelligence in decision making. Organisations are making use of big data from social media sites like Facebook and twitter as well as search engines to fine tune their business strategies.

  • Big data and natural language processing techniques are being used to evaluate consumer responses leading to improved customer service.

  • The use of big data enables organisations to identify risks to product or services well in advance.

Essentially, there are numerous applications of big data in different sectors with lots of benefits. 

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