As businesses compete, the impacts of Big Data can give founders an edge in the ever-changing landscape
Opportunities for Big Data-Every day three quintillion bytes of data is generated. This data comes from different sources like digital pictures, videos, posts on social media, e-businesses, intelligent sensors, and log storage in the IT industry.
According to McKinsey, “big data” refers to datasets whose size is far beyond the ability of typical database software tools to capture, store, manage and analyse.
Real-world challenges of Big Data enterprises
One of the major sources of data is the log storage, which is present in the IT industries because the IT industry stores a lot of information in the form of logs of data.
This data is so vast that the traditional system becomes unable to handle such kinds of logs as this data is semi-structured in nature and is growing with great velocity.
Sensor data refers to the data coming out of sensors. An enormous amount of sensor data is also a challenge for big data. One example of sensor data is the Large Hadron Collider (LHC).
LHC is the world’s largest and highest-energy particle accelerator. The data-flow in its experiments consists of twenty-five to two hundred petabytes of information that has to be processed and held on.
So we can say that this sensor data is a very challenging one for management as the traditional system cannot handle such a variety of data.
Another place where we can find big data is in Risk Analysis.
So any financial institute needs to model data, and based on this data, they need to calculate what kind of risk can occur.
One of the problems with the data of risk analysis is that it is huge and is generally under-utilised. We need to perform big data analytics on such data to get more accurate information and predictions on risks involved in the management of risk analysis data.
The data generated from social media can be of any type—may be structured, semi-structured or unstructured.
The rate at which social media data is increasing is astounding. Therefore, it is also one of the important sources of big data in a real-life scenario.
Apart from the above scenario, there are some other significant data contributors as well; for example, customer analytics, experience analytics, threat analysis, fraud analysis, and brand sentiment analysis, where we use big data.