Big Data
5
Most Common Myths about Big Data
Is Big Data all about data volume explosion? or is it just limited to catering data acculation through social media feeds? The steady influx of information is not so hard to grasp! To understand Big Data better lets discuss the top 3 myths that are going round the corner!
Given the immense amount of information collected about us every day, can this “trailblazing” dose of technology really help entrepreneurs, researchers and most importantly public?
Data befits Big Data when its Volume, Velocity or Variety surpasses the abilities of your IT systems to ingest, store, analyse and process it.
It is quite apparent that IT infrastructure is not a homogeneous mass, each of the functional business groups have their own unique business processes and the large entwined business data to deal with.
Things go complex when with the increasing volume and faster flows of data, they lack the ability to ‘mine’ it and derive the true business intelligence in a timely fashion.
The only solution to handle the avalanche of data needs to be fully virtualised, fully automated and holistically managed with a pervasive connectivity.
Big Data differs from constricted applications that focus on selective sources of data. Big Data probes through a broad range of sources that include structured information (CRM data and intelligence data from industry partners etc.) as well as unstructured information derived from social media (information gleaned from social media feeds, blogs, videos and other sources).
Efficiencies are obtained through convergence of the data and infrastructure to meet the functionality that needs to be delivered.
One of the prime features of Big Data includes adding mobility to data, which means blending data in motion (unstructured data) with data at rest (structured data) and also collecting
real time data from the field adding to the pool of knowledge that will drive insights in another part of the system. In the scenario when companies are completely data driven, mobility accentuates the impact of big data on both customer intelligence and operational efficiency.