Difficulties include capture, storage, search, sharing, analytics, and visualizing. This trend continues because of the benefits of working with larger and larger data sets. Though a moving target, current limits are on the order of petabytes, exabytes and zettabytes of data.
One current feature of big data is the difficulty working with it using
relational databases and desktop statistics/visualization packages,
requiring instead "massively parallel software running on tens,
hundreds, or even thousands of servers". The size of "big data" varies depending on the capabilities of the organization managing the set.
Big Data Examples:-
- YouTube streams millions of videos on multiple channels
- Facebook handles 40 billion photos from its user base.
- Twitter handles tweets of billion users and even more
- Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes of data
