9 Lessons Learned: Resources

What You Should Know About Big Data

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 companies use this concept as a marketing trick and even utilized out of context. Luckily, you can learn what you can about big data here and then learn more of its being useful in being used as a tool to solve a number of 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. The everyday lives of people have been greatly affected and influenced positively by these achievements in science. What then becomes challenging will be the taking of measurement of data that is not static. The term non-static is employed among objects and things that get to constantly change in real time at volumes and rates that are bigger than anyone can imagine. Utilizing some computers seems to be the only viable option in being able to process such crucial date.

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. Here are some of the descriptions of big data that you need to know.

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 the classification of variety, this is the identification where your data is a part of in terms of category that is being determined by the data analysts. 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 must be done by these people in order for them to give more value to their data as well as be able to use what they have obtained effectively and to their benefit. Velocity is then more about finding out how to put to good use how fast the processing and generating of data are being done. For data analysts, you can find in them the crucial role that variability plays as well. And last, veracity is about what quality the data captured has. The veracity of your big data will be identified based on how accurately the data analysts have done an analysis of your veracity.

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