“Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard, Senior Vice President, Gartner Research
The world is now recording more data than we are capable of processing. Over the next four years, the amount of digital data produced will exceed a staggering 40 zettabytes, which comes up to 5,200 GB of data for every man, woman and child around the world, according figures from a Digital Universe study.
To give these numbers some perspective, Lucas Mearian, Senior Writer for Computerworld.com, highlights that 40 zettabytes is the equivalent of 40 trillion gigabytes, “estimated to be 57 times the amount of all the grains of sand on all the beaches on earth,” he says. Mearian also points out that to hit this figure, global data is expected to double every two years until we enter 2020.
As an impactful institution, the University of Queensland (UQ) is doing what it can to help us understand Big Data through intricate analytics. The University achieves this through the development of data fusion methods, allowing students and academics to ‘connect the dots’ and derive a global picture, from small-to-big, of certain situations; from market feedback on particular products and services, to overviews of patient medical conditions, to overall business performance, and even to trending social opinions in communities and various social networks.
“Social media is now part of human life. It has been seen that performance of organisations can be influenced by social opinions,” notes Professor Xue Li, a UQ expert in Intelligent Web Information Systems. “For example, government elections, local housing prices, and stock market shares are all influenced by people’s attitudes, feelings, and moods,” Xue Lin explains.
“Therefore, if we are able to accurately capture people’s sentiment and opinions expressed on social media toward certain objects, we can then predict changes of performance with respect to the changes of peoples’ opinions.”
Most Big Data applications incorporate three essential aspects: Big Data Fusion, Big Data Analytics, and Big Data Visualisation; one way UQ is striving to analyse Big Data is through the Data and Knowledge Engineering (DKE) research division of the School of Information Technology and Electrical Engineering (ITEE). Here, Professor Xiaofang Zhou and his team of experienced academics are working at a world-first level on all three of these aspects in projects funded by the Australian Research Council (ARC).
“In dealing with the well-known three big- ‘v’ (volume, variety, and velocity) properties of Big Data, we are facing new challenges,” Professor Xue Li adds. “Firstly, traditional sampling and modelling theories are challenged: how much data ought to be enough for analysis? Should a solution be computed on the fly or simply searched over a large data space?
“Secondly, as in high-dimensional data space, every object would be an outlier, can we design algorithms and indexes to work with a large volume of high-dimensional yet sparse data efficiently,” he explains. “Thirdly how can we design and implement algorithms that optimise the usage of Tera-byte scale memories in current cloud computing platforms?”
To answer these questions and meet industry requirements, 2017 will see the introduction of UQ’s brand-new Master of Data Science program, one of few around the world to combine cross-disciplinary academics with direct industry contact, and a wealth of practical experience within the exciting, and ever-expanding, Data Science field. Students will pursue advanced topics, from computing to statistics, mathematics to business, finance to health, and beyond.
Using relevant Big Data tools and technologies to nurture crucial knowledge surrounding the ethics of data use, as well as the legal considerations, communication, and more. Graduates will leave instilled with elite technical expertise, as well as a strong capacity for creative and disruptive thinking. Students will be ready to solve the most pressing issues within global Data Science, propelling graduates to the height of employability within one of the world’s most in-demand professions.