It?s been a long while since William Caxton set up his first printing press in Westminster and provided a mechanism to help spread the written word that would eventually strike at the heart of Reformation England. Caxton?s invention in 1483 allowed for the mass production of printed matter which, in time challenged the authority of the established church, lead to the publication of?the King James Bible, and brought about the Age of Enlightenment and the Industrial Revolution.
William Caxton, inventor of the printing press
Today, we are standing on the shoulders of this great giant.?As Caxton transformed important words into powerful messages through innovation in technology over 500 years ago, so we now must learn to do similar with big data ? that?collection of?data sets?so large and complex that it has become difficult to process using on-hand database management tools -?in the 21st century.
But, is the time right?
We?ve now had around 20 years of the commercial Internet with organisations embracing innovation to find new markets globally, provide a better service to their customers, simplify processes, and generally make life easier. The explosion of social media has made our personal and business relationships more interactive online, but we are faced with the enormity of information overkill that makes any informed decisions difficult.
How do we make sense of big data,?prioristise what?s important, value and secure it?
Start-ups are among those best placed to make the most of new technology, but they may be stopped in their tracks by more established players who will protect their own interests. Many small businesses will find it difficult to defend legal challenges to intellectual property rights or stop large corporate organisations from using IP laws to restrict consumer behaviour in particular markets.
Dealing with big data brings a whole plethora of legal problems such as intellectual property rights; interoperability; licensing; platforms and processing, and services out. Who is responsible for big data, is it accurate and will algorithms that drive the data be accessible or remain commercially sensitive? Can we anonymise data so that it doesn?t breach privacy and data protection rules?
A 2011?McKinsey?report?suggests suitable technologies include?A/B testing,?association rule learning,?classification, luster analysis,?crowd sourcing,data fusion?and?integration,?ensemble learning,?genetic algorithms,?machine learning, natural language processing,?neural networks,pattern recognition,?anomaly detection,?predictive modelling,?regression,?sentiment analysis,?signal processing,?supervised?and unsupervised learning,?simulation,?time series analysis?and?visualisation.
Additional technologies being applied to big data include massively parallel-processing (MPP) databases,?search-based applications, data-mining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.
But whilst big data may be difficult to work with using relational databases and desktop statistics and visualization packages, requiring instead massively parallel software running on tens, hundreds, or even thousands of servers, let?s not forget the end game. Everything organisations do, irrespective of size or sector must be viable financially and serve the bottom line. Solutions therefore need to be scalable and reflect the value in the big data being collected.
Caxton?s simple printing press changed the world. We?ve just got to make it a smarter planet.
Source: http://www.eradar.eu/2012/11/legal-challenges-big-data/
the lion king suzanne collins cherry blossom festival nc state erika van pelt pat robertson hunger games trailer
No comments:
Post a Comment