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The topic today will resolve around big data, example will be showed and the challenges that face by big data researcher and practitioner Â
A petabytes is a lot of data, 1 petabytes is equal to 13.3 years of hd tv content, imagines the amount of video you can download.
 "Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization (Douglas, 2012)
http://etomicmail.com/blog/wp-content/uploads/2013/03/big-data-infographic.jpg
To shrink it down it just basically is a huge amount of traffic data collected through the web and used to the full benefits of itself. The amount of data changes constantly, but will not go down only will increase in quantity.
The trend to larger data sets is due to the additional information that constantly being feed from analysis of a single large set of related data, allowing the result to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions. Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set (Jacob, 2012).
Comparing big data with web 2.0, it simply gather information data from a larger and demanding sources which are more inclusive to our personal lives.
Wal-Mart Stores Inc. and search. The mega-retailer's latest search engine for Walmart.com includes semantic data. Polaris, a platform that was designed in-house, relies on text analysis, machine learning and even synonym mining to produce relevant search results. Wal-Mart says adding semantic search has improved online shoppers completing a purchase by 10% to 15%. "In Wal-Mart terms, that is billions of dollars” (Laskowski, 2013).
Facebook, which I believed most of you are intrigued to use right now has over 901 millions active users generating social interaction data. And even 5 billion of people are using their mobile phones as of now.
But nothing comes without challenges. The challenges of capture, curation, storage,search, sharing, transfer, analysis and visualization (Vance, 2012)
Even in practical sense, the data are more empirical to certain information company that are restricted access from the public. The ethic issue and the lack of talent on analysing data (Woodford, 2014)
Big data is difficult to work with using most relational database management systems and desktop statistics and visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers
Although challenges are faced, we as human always come up with simpler way to finish our business.
With twitter hash tag implementation, researchers are more convenient to investigate a certain topic which are more accessible and easier to analyse.
So in the end, the question of privacy are introduced. What would you share in consideration of these factors?
 Reference List
Laney, Douglas. "The Importance of 'Big Data': A Definition". Gartner. Accessed on 4 May 2014.
Jacobs, A. 2012. "The Pathologies of Big Data".ACMQueue. Accessed on 4 May 2014. http://queue.acm.org/detail.cfm?id=1563874
Vance, Ashley. 2010. "Start-Up Goes After Big Data With Hadoop Helper". New York Times Blog. Accessed on 4 May 2014. http://bits.blogs.nytimes.com/2010/04/22/start-up-goes-after-big-data-with-hadoop-helper/?_php=true&_type=blogs&dbk&_r=0
Laskowski, Nicole. 2013. “Ten big data case studies in a nutshell.” Accessed on 4 May 2014. http://searchcio.techtarget.com/opinion/Ten-big-data-case-studies-in-a-nutshell
Woodford, Darryl. 2014. “New Media, Big Data & Telemetric: Week 9 lectures notes.” Accessed on 4 May 2014













