Let's talk about what is the difference between normal data analytics and big data analytics. In case, like in traditional data analytics, what we call what the data analyst. They used to just find out patterns on a support of the data set. They'd never explore the data set. They will just take some random samples or maybe they would apply some kind of algorithm and choose some sub portion of the data set, then they could perform the data analytics. The results, they were not very accurate because they were just based on some portion of the data analyst. But if we are going for approaches such as big data analytics, what it does is it will scan and it will go through the entire dateset or if not the entire datasets, it will go through a larger dateset and then it would perform the analysis.
Questions About Big Data Analytic:
- Why should one go for big data analytics?
- Why should we not just rather go through a small amount of data set and find out the answers, find out the patterns and perform our analytics?
- Why do we have to just go for big data analytics?
- Why not the traditional ones?
According to a survey which was conducted by Pew Research Big Data Analytics. What they found out was that the major reason for this kind of usage of big data analytics is it could provide better decision making.
Example of Big Data Analytics:
If you click or you go to an Amazon Web site and you like a particular kind of book. Next time when you are surfing the Internet, what you can see is that. There will be a kind of pop up will up here that will such and such book is available with this much kind of discount. These things are all the applications of big data analytics which are being used here. In case of recommendations or in case of recommender systems.