The word Big data refers to a large collection of data, A volume so massive, that the traditional tools are unable to handle it. And it is keeping up the growth increasing by each passing moment. Imagine a huge set of data generated by everyone who uses an electronic device connected to the internet. Yes, all that data from all the devices are considered part of big data.
For handling and utilizing big data there are different requirements which sadly do not match the traditional processes. For understanding how it is influencing commerce as a whole, we must first dive into the structural and characterizing aspects of big data.
There are three prominent types of big data in terms of structure.
- Semi structured
Structured Big data
Structured Big data is a form of big data which is easily readable, easy to figure out and organized to a certain extent. For example, A list ( excel sheet ) containing the salary details of employees is a form of structured data.
Unstructured big data
Unstructured big data is mostly considered usable and extractible but with more difficulty and effort. This kind of big data needs indirect methods of extraction and analysis. For example, Data presented in video or text can be considered unstructured as the organization of these kinds of data is way more primitive than a sheet containing salary details.
Semi structured Big data
Semi structured Big data clearly sits in the middle. XML files are a good example of semi structured Big data. These types of data sets are relatively open for extraction and utilization but still require skill and a variety of methods for proper execution of processes involving it.
Key characters of Big data.
Volume of Big data is phenomenal. It contains all the data from commerce to scientific data generated by you and me. Large storage systems and unconventionally powerful computers are required to handle such volume.
Variety of big data can not be measured by ordinary systems. As it contains all kinds of data there can be.
Velocity of Big data generation is unsurprisingly extreme. It is growing all the time at a rapid rate. For example, Newyork stock exchange generates one terabyte of trade data every day.
Variability for big data stands for inconsistency. Multiple aspects of big data are inconsistent in nature depriving the user of a standardized protocol or system of handling. As new data sees the light every day the handling method must evolve in order to cope up.
How Big data analysis is changing the market ?
The change introduced by big data is mostly in the form of predictability and prescribing abilities. Now a day with proper Big data training an analyst can predict trends in the market with the help of patterns seen previously. Before the onset of any kind of business, ideas can be derived with the help of big data. Access to big data can reveal the needs of a population in a given region alongside how much they are willing to spend. In a nutshell, the certainty factor is added to commerce by the utilization of big data.