Big Data with R Big Data refers to the large volume of data which may be organized or unorganized. This big data is very essential for large organizations and businesses for valuable insights to determine futuristic trends. Big Data is defined in terms of 3Vs which are as follows: Volume – Volume refers to the quantity and amount of data and this data is increasing day by day. Facebook has more number of users than the entire population of China. Its data is also huge. The data is in the form of images, music, videos and all such stuff. Velocity – Velocity refers to the rate at which the data is generated. Again taking the example of Facebook, a huge amount of data is uploaded, shared each second on Facebook. People on social media want new information and content each time they log in to social media. Old obsolete news and information does not matter to them. Thus new information is shared at every second on social media. Variety – Coming to the third V of Big Data i.e. variety. Variety means diverse type of data. There are multiple formats of data that can be stored. The data can be in the form of image, video, text, pdf or excel. Big Data has a big challenge of managing this different type of data. An organization need to arrange similar format of data together in order to extract important information out of that.
Why is Big Data Analytics important? Big Data and its analytics are important on account of the following reasons:
Reduction in Cost – Big Data Analytics offer cost advantages using technologies like Hadoop and Cloud Computing. These technologies help in storing and managing large amount of data.
Better Decision making – Using Hadoop and analytics, organizations and businesses are able to make better and faster decisions by analyzing different sources of data.