The Internet of Things will create new types of data, and for an executive at business intelligence provider SAS, having staff that can analyse and interpret these varied data types will be the key to ensuring a return on IoT investments.

“The Internet of Things will create even more big data than we currently experience, and in the IoT world, we make the distinction between streaming data and persistent data,” said Lynette Clunies-Ross, chief operating officer at SAS Australia.

“Because of the sheer volume of the data, there are architectural and design decisions that need to be made around where we apply the analytics and the decision-making, whether it be at the edge of the network or in the cloud.

“Another dimension is pattern recognition, to identify signals from the noise, and lastly there’s a need for understanding the process integration piece, because IoT really becomes embedded in what we call the ‘systems of systems’.”

Clunies-Ross also believes that data scientists need more than analytics expertise to be effective in the IoT world.

“Within SAS we put a lot of emphasis on business acumen and communication skills, as we believe those are very important for the effectiveness of a data scientist,” she said.

“When we train our data scientists, we take a case study approach to focus on how the analytics adds value to the business process.

“But this business focus really started a several years ago, when SAS made the decision around developing solutions, and that’s come from working with CSOs, CMOs, chief risk officers and business leaders.

“Without that, analytics is just a tool. What brings it to life is how it’s applied to business problems and to achieve business outcomes,” she added.

Addressing the data scientist drought in Australia

Clunies-Ross acknowledged that data scientists in Australia are in short supply, but added that this could have a positive effect on the industry.

“I think that scarcity could drive innovation to automate what we can and focus our rare talent on critical design elements,” she said.

“As the promise of IoT moves to reality, the groundswell will drive innovation in business models and how we leverage our talent.”

Still, Clunies-Ross concedes that having more data scientists would be a good thing, and to this end SAS has established a local branch of the SAS Academy for Data Science.

The academy provides two levels of qualification, the ‘Big Data Professional’ and the ‘Advanced Analytics Professional’.

Each level comprises of six weeks of content and combines classroom and live web instruction with hands-on case studies, team projects, coaching and related certification exams.

Completion of either level provides the student with the SAS Certified Data Scientist title.

“The academy was developed by SAS’s global education practice in the US, and it was created in response to the gap in data scientist talent that was seen there, and the need to accelerate pathways to certification,” said Clunies-Ross.

“We decided to launch it in Australia in response to a similar local demand for big data professionals and data scientists locally.”

The Australian academy is also working with education institutions, such as a joint certificate program with the Melbourne Business School, which offers an SAS-supported Master of Business Analytics degree.

Clunies-Ross said that collaboration with education providers has been a core tenet of the company since its inception.

“Here in Australia, we’ve had a long history in all of the universities to embed the SAS analytics curriculum into the relevant undergraduate courses, and partnering with certain universities for post-graduate courses,” she added.