The cloud is changing the world of analytics, Microsoft’s Colin Masson tells IT Contributing Editor Malcolm Wheatley.
Analytics is hot. Big Data is hot. And the combination of the two is even hotter. But so far, a lot of the gains derived from combining the two have tended to be among manufacturers at the larger end of the size spectrum.
But it doesn’t have to be that way, stresses Colin Masson, Microsoft’s global industry director for manufacturing and distribution. How so? Because the world of technology has changed, and with it the whole analytics and big data paradigm.
“It wasn’t so long ago that you needed big computers, big budgets, and big brains to do big data, which restricted it to large companies with teams of increasingly scarce and expensive data scientists,” he points out. “Now, even the smallest manufacturer can get started—and for just a few pounds per month.”
The reason, of course, is the cloud. And the cloud, explains Masson, has changed the equation in two important ways.
First, it’s a source of high-powered computer processing power. And, importantly, computer processing power that manufacturers don’t need to physically own in order to be able to use. Simply rent the computing time required, on a low-cost pay-as-you-go basis.
And second, because the cloud also provides access to high-powered applications which can process all that data — applications that can also be subscribed to, rather than bought outright.
The latest generation of analytics software has never been more intuitive and easy to use. Which for ordinary mid-sized manufacturers, where Ph.Ds in data science are scarce, can be a huge plus.
But if the era of “big computer, big budget, big brains” big data analytics is firmly in the past, manufacturers can certainly be forgiven for asking themselves if they actually possess the requisite big data in the first place.
Masson’s emphatic answer: they do. Take manufacturers’ ERP systems, for instance. Microsoft Dynamics ERP user JJ Foods, he points out, is mining the sales data held in its ERP system and combining it with externally-sourced weather and demographic data in order to gain insights into product demand.
The ERP data is held in-house, he stresses, but the analytics is done in the cloud, leveraging a suite of applications running on Microsoft’s Azure cloud platform.
Likewise, he adds, another source of big data is that which is presently locked away inside a myriad of devices: devices on manufacturers’ factory floors, devices belonging to their customers, and devices in their upstream and downstream supply chains.
And while the Internet of Things serves as a conduit to make that data accessible for analysis, it’s the cloud that is transforming the costs and ease of that analysis.
Lido Stone Works, for instance, leverages Microsoft’s Azure Intelligent Systems Services to monitor the machinery that it uses in its production processes, which — like sales analysis — is one of the core analytics scenarios that Microsoft sees being utilised in manufacturing.
“It’s condition monitoring, remote diagnostics and predictive maintenance rolled into one — all without requiring access to scarce and remote experts, or requiring manufacturers to purchase large expensive computers,” sums up Masson. “In short, it’s the future.”
