Understanding Big Data Better
When it comes to the information technology industry, you will see that the concept ‘big data’ is making a lot of buzz. 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 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.
Mathematics and Physics are the two things that help in calculating what exact distance can be obtained from the West Coast to the East Coast of the country. This is a very important development in the world and has been used in a wide range of technologies in the lives of people. 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. For this kind of data, there is no better way to get things processing than with the use of computers.
Big data is made up of four dimensions based on the studies done by IBM data scientists starting with volume, velocity, veracity, and variety. However, there is still more to big data than those four aspects. What you will see after are the identifying characteristics that make big data what it is now and what it entails.
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 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 the aspect that deals with determining how fast the date is processed and generated to become useful. 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. For accurate assessment of your big data quality, it will have to depend on how much veracity your source data has.