Week 3

In the last week, I understand what is big data and do some research about  Apache Spark and Apache Hadoop.

Big data

The amount of data on the internet is in the order of exabytes and it becomes  (10^18 bytes) and such huge data sets are what you call big data. For instance, Google, Youtube, Facebook, and many other sites contain lot contents being uploaded by a lot many users, lots are shared, comments given on post and much such activity occur every minute from all over the world. We call ‘Big Data ‘, which always keep increasing at exponential rates. Big Data Hadoop is called a huge amount Of Data. It is also structured and Unstructured Data. Big Data Hadoop Is defined to Five V’s Of Big Data Hadoop. Volume, Velocity, Variety, Value, Veracity.

Volume: The meaning of volume is measured by information produced every second. Simply think about every one of the messages, twitter messages, photographs, video cuts, sensor information and so on we deliver and share each second.

Velocity: Speed can really compare and it is just the speed at which data is generated.

Variety: The third V is called a variety. Any company can get information from a wide range of sources: from in-house gadgets to cell phone GPS innovation or what individuals are stating on interpersonal organizations. The significance of these wellsprings of data shifts relying upon the idea of the business.

Veracity: The fourth V is veracity, which is equal to quality. We have every one of the information, however, would we be able to miss something? Is the information clean and precise?

Value: The extraction of useful data from huge amount of data is called value.

Some Use cases of Big Data

• Amazon is the biggest Use case of Big Data. Each and every click you do on their website is recorded, analyzed and the next time you visit you will come up with the best deals and prices for the items one checked and looked. You may also get emails with such offerings. It records your IP your location your social media accounts etc. This is done on a real-time basis.
• Analytics for Fraud Detection: Banks can find an unusual card behavior in real time (if somebody else, not the owner, is using it) and block suspicious activities or banks can at least postpone them to inform the owner.