Big Data and Predictive Analytics Week 10 Blog Tianxiang Yu (Anthony) N8030715
Now the world has become into a digital era of information explosion, data is generated around us all the time. With the widespread popularity of social networks, each internet user has become a major part of data collection. Any operation by users on the internet, could be used to understand their character, habits, and even values. Thus, the increasing amount of big data affects and changes peopleâs personal life and work in some aspects.
 Facebook's director of engineering Jay Parikh explains the significance of big data: âBig data really is about having insights and making an impact on your business. If you arenât taking advantage of the data youâre collecting, then you just have a pile of data, you donât have big data." (Cohen 2012)
 âBig dataâ has been existed in the industries of science, military, communications, finance and others for a long time. But the internet is only rapidly developed in recent years, and the new media in film and TV industries is now just showing up its advantage. In the film and TV industries, nothing is certain. A film and TV production may have found all the great directors, actors and screenplay of popular themes, but the results is still unsatisfactory. However, prediction is power (Siegel 2013). According to Siegel (2013), âPredictive analytics (PA)-Technology that learns from experience (data) to predict the future behaviour of individuals in order to drive better decisions.â
 PA leads within the growing trend to make decisions more âdata drivenâ, with empirical evidence. PA is the means to drive per-person decisions empirically, as guided by data. Predictions drive how organizations treat and serve an individual, across the operations that define a functional society. And, PA is a completely different from forecasting (Siegel 2013).
 American TV series "House of Cards" is a successful example of "custom" TV show based on data analysis.
It's presented and brocasted by Netflix. Every day, Netflix user traffic averagely contains 30 million users, 4 million comments, 3 million searching requests. From the audience insight, targeting, every step is guided by accurate and detailed data analysis, which is decision produced by user demand (Armina 2013).
YouTube Video: The Risk Behind Netflix's Original Programming Leap
 It seems that Netflix knows what audience like to see. From their database, they have been known audience like director David Fincherâs film, Kevin Spaceyâs performance, British version of "House of Cards" (running 1990) is popular.
Eventually, what to film, who is gonna direct, who is gonna act, how to broadcast, all the decisions are made by millions of audienceâs personal preferences (Carr 2013). Netflix's former VP of communications Steve Swasey said âWe donât have to spend millions to get people to tune into this, through our algorithms we can determine who would be interested in the showâ(Ryan 2011).
 From a marketing point of view, excavate and analyse habits and preferences of users from complex data, find out the products and services which fit the "taste" of users more, and combine with userâs needs to adjust and optimize the product and services specifically, that is the value of big data.
References
Armina, Ligaya. 2013. âNetflix ready for onslaught: CEO; Competitors developing own servicesâ. National Post, May 15.Â
 Carr, David. 2013. âGiving Viewers What They Wantâ. New York Times, February 24.Â
 Cohen David. 2012. âGabriel & Co. is looking for a Social Media Coordinator. Facebook VP Of Infrastructure Engineering Jay Parikh Talks Big Data, Project Prismâ. AllFacebook, August 23.                Â
Keating, Gina. 2014. âMyths and realities Netflix finds higher demand for old movies and TV showsâ. South Florida Sun â Sentinel, Feb 22.Â
 Ryan, Lawler. 2011. âHow Netflix Will Use Big Data to Push House of Cards.â Gigaom, March 18.Â
 Siegel, Eric. 2013. Introduction: The Prediction Effect. In Siegel, Eric, Predictive analytics: the power to predict who will click, buy, lie, or die, (pp.1 - 16). Hoboken, NJ: Wiley.












