A survey on various challenges and aspects in handling big data

The data which are very larger in size and which cannot be maintained in terms of Mega Byte (MB) and Giga Byte (GB) are termed to be as Big Data. The big data usually sizes in Peta Byte (10
^Λ
15). Research says that the data which is referred as big data in today's life is the data that has been collected from the past three years. The resources for the big data are social networking sites which collects vast data from face book, twitter, linked-In where billions of users post the data in a daily basis. Share markets also contribute to the big data with the process of stock exchanging and also by collecting data through the share transactions. E-commerce sites collect the data which can be useful for the service providers to introduce the goods and items that satisfies the user requirements. The other resources for the big data are weather station, telecom companies and etc. The three important features of big data are Velocity, Volume and Veracity. The size of the big data is increasing in a very rapid way so that the data doubles for every two years. Big data is sometimes structured data and sometimes unstructured data. The data that can be maintained in a table structure or with rows and column, then those data are called as structured data. The data from CCTV footage are the examples for the unstructured data. In this paper, we attempted to discuss the growth, life cycle stages, handling of huge data on Hadoop framework, publication frequencies, advantages and challenges in handling big data.