9 Lessons Learned: Resources

What You Should Know About Big Data

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’. 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. Its real meaning gets lost because of it becoming a major gimmick being used by most companies to lure more customers to make deals with them. 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. 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. 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. But then, big data cannot just be classified into these four factors, there are still other factors that are part of it. 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 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 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. Variability will be another factor worthy of consideration among data analysts. And finally, you have veracity that identifies the captured data quality. The veracity of your big data will be identified based on how accurately the data analysts have done an analysis of your veracity.

A Simple Plan: Businesses

A Simple Plan: Businesses