Big Data is taking the world by storm. Since a huge amount of data is originating from a large number of digital resources, the importance of analytics has suddenly grown. It is helping companies to analyze in order to make most of all that data which has been considered useless all these years.
But do all people in industry really know what big data is?
Big data; as the name suggests, is big. Any data which is structured or non-structured that can be broken down into patterns for mining is considered as big data. The benefits of big data include timely insights from diverse data sources, management of a huge amount of data, better insights about unstructured and semi-structured data, and most importantly, decision making.
Big Data has been catering to different industries and taking them on a success oriented journey. In healthcare, big data is helping in tracking a patient’s record, which is useful for the physician itself. Since technology is increasing at a rapid pace, the cost associated with the health care industry is also increasing. No one ever thought that it would be possible for a doctor to treat his patients remotely, but with the evolution of big data oriented medical devices, a doctor can now remotely prescribe medicines/treatment by monitoring a watch fitted to patient’s hand.
Other major benefits of big data are fraud detections, especially in the banking sector. All the fraud and mischievous tasks performed can easily be tracked by the implementation of big data. It detects the misuse of credit cards, misuse of debit cards, archival of inspection tracks, venture credit hazard treatment, business clarity, customer statistics alteration, public analytics for business, IT action analytics, and IT strategy fulfillment analytics.
High degrees of integration. Well-designed ecosystems. Unified architectures. Data and analytics centricity. That short list doesn’t necessarily require every component or technical detail to make big data programs function. But certainly these are difference-making attributes that ensure big data programs work effectively.
Written by Moorat Gopichand