Understanding Big Data Better
The term ‘big data’ has become a huge trend in the world of information technology. You might have heard about this term because a lot of people in the IT industry are making a bigger buzz about it just to impress other people usually without them even knowing what it means exactly. Most companies use this concept as a marketing trick and even utilized out of context. Good thing all the answers to most questions people have on big data will be answered here along with how they can be used to find a solution for most complicated problems.
Mathematics and Physics are the two things that can give people the exact information about the distance between the East Coast to the West Coast. These two things have made it very much possible for the great achievements that are being used across technologies as people live their lives on a daily basis. What then becomes challenging will be the taking of measurement of data that is not static. What makes non-static data very difficult to obtain is their being able to change rapidly in volumes and rates that get to happen constantly and in real time. For this kind of data, there is no better way to get things processing than with the use of computers.
Based on findings of data scientists working for IBM, they have concluded that there are four aspects of big data, namely variety, veracity, volume, and velocity. And yet, these four aspects are not just what big data is all about. If you want to learn more about big data, do not forget to look into the following characteristics for them.
One of the ways to find out about your data being really called big data is to take a look at its volume and analyze its sized in association with potential and value if it is really to be called big data. With big data, data analysts must make sure to look at what classification the data is a part of and this the aspect of variety. This aids in the people who are the ones assigned in associating the data and then analyzing them to the best of their intentions. This data helps in letting the people utilize such data to their own advantage and thus, putting more importance to this particular data. Velocity is then more about finding out how to put to good use how fast the processing and generating of data are being done. The aspect of variability is also crucial to determining what problem data analysts might be coming across. And finally, you have veracity that identifies the captured data quality. Proper analysis of the big data will then be done in finding out what kind of quality your data source has.