As we’ve reported previously, the Internet of Things is changing data science, and a visiting executive from analytics company SAS went into further detail into how IoT along with artificial intelligence is reshaping the industry.
Oliver Schabenberger is the executive VP of SAS’s research and development division and recently appointed CTO, and was recently in Sydney to discuss updates to the new SAS Viya analytics platform and to share his thoughts on the future of the analytics industry.
He said that IoT has led to the increasing importance of edge analytics, with data now being observed on a continuum, requiring differing techniques to be deployed depending on observation point, accuracy and speed of data movement.
“We can no longer just think about processing data in the cloud; we also have to think about event stream processing,” he added.
He also said that analytics software is quickly transitioning into the cognitive space, where sensing, listening and gesturing will become common forms of input, and reading and writing of human-like responses will become common forms of output.
“Now we expect things to adapt, to learn, to be ubiquitous, to be situationally aware, and be historically aware,” he said.
“We’re replacing processes that are very deterministic and rule-based with automated, self-learning processes.”
Schabenberger said that traditional statistical modelling, where humans would select a model they believe would best fit the data collected, will be replaced by data-driven machine learning.
However, he believes that there are two types of machine learning, classical and modern.
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