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Understanding Big Data Better

The term ‘big data’ has become a huge trend in the world of information technology. A lot of IT companies are always making mention of it more so just to impress others even if they do not have the slightest of ideas what the entire concept is all about. Most of the time, the term is misconstrued, and it has become a major gimmick to market the company in more ways than one. 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.

If you want to learn more about the distances of locations and countries, you need to understand that calculations are carried out by the use of Mathematics and Physics. 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 remains as a challenge will then be getting the measurements using data that is not static. If you say non-static, you are referring to some things that are changing at a constant pattern and in bigger volumes and rates in real time. The best method to obtain such a particular kind data will be 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. But then, big data cannot just be classified into these four factors, there are still other factors that are part of it. Here are some of the descriptions of big data that you need to know.

In terms of volume, this is the data size that will determine if the potential and value of your data can really be thought of as being big data or not. 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 is proven to be very helpful in finding out what the date is all about and what might be associated with it. Such data has been proven to be very beneficial among these people for use to their own advantage in more ways than one. Knowing how fast the data will be processed and generated if it is useful enough is also the doing of velocity. For data analysts, you can find in them the crucial role that variability plays as well. The quality of the captured data will then be identified as the aspect of veracity is being kept in mind. For accurate assessment of your big data quality, it will have to depend on how much veracity your source data has.

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