There was a time when data wasalways discarded because of unavailability of storing space, lacking ofanalyzing tools etc. However, Big Data term plays a significant role in today’slife because almost everything adds on to available data to make it huge forcapturing, storing and analyzing. In exemplification, Facebook generates 10 TBdaily, Twitter generates 7 TB of data daily and IBM claims 90% of today’sstored data was generated in just the last two years. Due to availability ofdata in more than one format and following factors are responsible for the considerationof Big Data:1) Increase instorage capacities: Nowadays, there are many approaches available for thestorage of Big Data such as Hybrid Cloud Storage which is a combination ofpublic cloud storage and private cloud storage, where critical data of aparticular organization can be stored in private cloud storage and rest of datais accessible through distributed public cloud storage.
Another possible approach that allows to very large sets of datais Object Storage. This acts as replacement of the traditional tree-likefile system with a flat data structure in which files are located by uniqueIDs, something like the DNS system on the internet. 2) Increase inprocessing power: Processing power can be increased by adoptingdifferent options like distributed computing which is a model in which differentcomputers or machines (nodes) are located on networked computers. Thesecomputers communicate and coordinate their actions by passing messages. All thecomponents interact with each other in order to achieve a single goal.
3) Dataavailability: The data volumes are exploding, more data has been created inthe past two years than the entire history of human race i.e. data is growingfaster than ever before which leads to availability of data in many forms. Forinstance – we perform 50,000 search queries every second, which makes 1.2trillion searches.
Besides this, we can see massive growth in video and photodata, where every minute up to 300 hours of video are uploaded to YouTubealone.4) Advancedanalytical techniques: Machine Learning is an example of advanced analyticaltechnique which gives computers the ability to learn without being explicitlyprogrammed. Machine Learning is ideal for exploiting the opportunities hiddenin Big Data. It is well suited to thecomplexity of dealing with disparate data sources and the huge variety ofvariables and amounts of data involved.5) Open –source software: In these days many open source software are availableto help us sort through Big Data. For example – Apache Hadoop, which iscurrently the most popular distributed file processing system. This system isbest known for its ease of use and its ability to process large amount of datain structured as well as unstructured formats. Its ability of replicating ofdata to nodes and making it available on local machine separates it from allother open – source software.
Abovementioned factors are the key enablers for the growth of Big Data in today’slife.
