Scalable software for the world’s growing data
It is estimated that 90% of all the world’s data has been generated over just the past few years, either through user-generated content or by scientific and industrial entities. Analytics software applications that are large scale and data intensive could extract important, usable insights from this large pool of big data, if they were systematically designed.
Ebrahim Bagheri, Canada Research Chair in Software and Semantic Computing, is addressing this pressing challenge by developing data analytics software platforms that can help us better understand the value and meaning of large volumes of data.
While most large-scale industries and government agencies tend to build data-intensive analytic applications, the speed at which data is being produced (over 25 million e-commerce transactions per second) transcends our capacity to manually manage it. The true potential of available data cannot be harnessed unless this data is systematically analyzed and aligned with core business or strategic objectives.
Bagheri’s research will equip software engineers and data scientists with the necessary tools to tap into this potential. In addition to pioneering new approaches to analyzing and understanding the value of data, Bagheri’s work is supporting the development of software that scales automatically, meaning it can react to changing data production and consumption patterns.
Bagheri’s innovative research is helping large-scale Canadian organizations build the most effective and efficient scalable software applications for their users, clients and customers.