Understanding Big Data Better

01 May

If you have been exposed in the IT industry for a long time, then there is no doubt that you have heard the words 'big data'. 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 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. This is a very important development in the world and has been used in a wide range of technologies in the lives of people. The only problem with measuring and calculating everything and anything there is now will be the non-static data. 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. Utilizing some computers seems to be the only viable option in being able to process such crucial date.

Big data is made up of four dimensions based on the studies done by IBM data scientists starting with volume, velocity, veracity, and variety. 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. To read more about the benefits of technology, go to https://en.wikipedia.org/wiki/Internet.

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. Data analysts will then do the task of identifying the variety of your data or the category in which it is a part of so that better assessment of the big data will be determined. This is beneficial for the people who are associated with it and are the ones assigned in doing the data analysis. 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.

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