A big data primer for Canadian businesses– what, why and who?

A big data primer for Canadian businesses– what, why and who?

Klaus Schwab calls it the Fourth Industrial Revolution, one that will “fundamentally alter the way we live, work and relate to each other.”

The transformation, the founder of the World Economic Forum boldly states, will be unlike anything humankind has ever experienced. He calls it a fusion of technologies that is “blurring the lines between the physical, digital and biological sphere. It is, he says, “evolving at an exponential, rather than linear, pace,” and is “disrupting almost every industry in every country.”

Imagine the possibilities, he says, with billions connected by their tiny portable devices, tremendous processing power, storage capacities, technological breakthroughs in artificial intelligence, robotics, 3D printing, nanotechnology, biotechnology and quantum computing, to name a few.

Big data is a big part of the digital revolution and companies that harness its potential will get ahead of the curve. The volume of data we generate in the industrial internet age is remarkable, but many don’t do anything with it. In the new revolution, it’s not the amount that’s so important — rather, it’s what organizations do with it.

Think, for example, about a railway provider. Jas Klotia, chief information officer for GE Canada, describes GE’s locomotives as rolling data centres, within which GE is capturing plenty of data through sensors and, through software applications, transmitting it back to GE’s highly skilled engineers for analysis. If the engineers can realize even one mile of efficiency by analyzing the data, they can increase earnings by up to 20 per cent. The same goes for aircraft engines — with a one per cent savings in fuel efficiency, the company can save more than $300 million.

Big data, in other words, is not small stuff. When GE talks about the “industrial internet” side of the “digital industrial revolution,” it envisions more than a billion smart meters installed in homes, transmitting valuable data on consumer behaviour. It sees more than 10 billion internet-connected light bulbs.

“You’re already seeing more than 150 million cars connected to the internet,” Klotia says. “If you think about the industrial internet, whomever can really master data and insights will be a winner and we’ve got to do this at high speed.”

GE estimates that the industrial internet could be a $225 billion market by 2020. Broken down, it estimates $125 billion of that will be in software applications, $100 billion in the software platform, or operating system. That means it will outsize the $90 billion spent on the consumer Internet of Things and the $70 billion spent on the enterprise Internet of Things.

Smaller companies are using the big data technology and knowledge to build service-based companies that help others access this valuable information.

Canada’s ThinkData, for example, is playing in the space. It collects government databases and “cleanses” the data (three references to the Canadian War Museum might have three slightly different names, making searching difficult so it standardizes those references and the formats in which the datasets come.) It then makes it available to its clients.

“Everyone is moving toward open data to make more educated decisions because the data is available,” says Bryan Smith, who was once a policy adviser to former Treasury Board President Tony Clement. “The problem is that not everyone has the resources, skills and expertise to grab the data, cleanse it, standardize it, build it into their models and keep it continuously updated.”

He said a data scientist is the highly specialized person who does the analysis. Many are actually data janitors because they are also tasked with finding the data, cleaning it, connecting to it and keeping it updated.

“We take care of the all the janitorial work to give the scientists clean feeds so they can focus on running models and doing analytics, all the stuff that is valuable to the company to make better decisions,” he said.

While some exporters would be ThinkData’s clients — companies that can make use of his cleansed data. ThinkData itself is also an exporter. Many of its oil and gas, financial services and real estate clients are based in the U.S.

Like ThinkData, GE’s big data customers in Canada include those from the oil and gas, rail, aerospace and energy management sectors.

Similarly, Vancouver’s Eight Solutions Inc. sells the Cumul8 product, a big-data solution that takes complex data and unlocks their potential — rather than just collecting the data, the company’s products analyze them and create a narrative. This puts the data’s usefulness to humans at the forefront, something that differentiates it from its competitors.

“We’ve brought our simplistic view of complex problems to bear with big data,” said Eight Solutions CEO Rory Armes. “If you collect data and put it into a narrative, you can start getting a predictive nature to that data.”

Armes says the company’s “data stories” engage its customers in ways that charts and dashboards can’t. Strong interactive visuals complete the package that ultimately offers customers a better understanding of data that they’re often already generating — and doing nothing with.

Eight Solutions – a Vancouver-based company – launched its products by working with the entertainment sector, but it has since expanded to industry. Lately, it’s been working with the forestry sector, for example, to develop “connected mills.”

“The mills are collecting more and more data from sensors,” Armes said. “In the case of a sawmill, you can use those data to determine, for example, that based on history, a machine, a saw, or a conveyer belt, will fail before it does. That’s information these companies really want presented in a readable way, even though they already have the underlying data to support it.”

Like ThinkData, Eight Solutions takes the data from a company’s sensors, cleans them up and gives the customer a web-based solution that lets it look and play with that data.

Armes’ company continues to work with customers in the entertainment space, but he’s also moving into transportation, though he can’t name his customers in those fields.

“Every industry is collecting more data than they know what to do with,” he said. “What’s needed is a tool set that transforms those data into usable information.”

Armes, who is exporting to India and the U.S., said his company has competition in the sector, but he also said it’s a “wide-open world when it comes to the data-narrative solution and I think this is an approach that companies will find invaluable from this point forward.”

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