Companies are using Big Data, but it’s more of a monitoring tool at this point than a tool for forecasting future trends, according to a recent report by GE and Accenture.
“Industrial Internet Insight for 2015” surveyed 250 executives from industrial companies about their use of Big Data analytics. According to OnWindows’ coverage, less than a third say Big Data is used across the organization for predictive analytics or in other ways that would optimize the business.https://o1.qnsr.com/log/p.gif?;n=203;c=204663295;s=11915;x=7936;f=201904081034270;u=j;z=TIMESTAMP;a=20410779;e=i
Still, 65 percent are using Big Data analytics as a tool for monitoring their equipment and other assets. This gives them an edge when it comes to preventative maintenance and detecting potential operational problems, OnWindows reports. The survey also showed that executives do feel pressure to adopt Big Data analytics — with 66 percent saying they worry about losing market position if they don’t act within one to three years.
A whopping 88 percent of organizations said Big Data analytics are a top priority.
Data Integration Matters Even with Managed Security Services
A recent report on the managed security services providers (MSSPs) market shows that data integration is a top concern for many would-be customers.
Elizabeth Leigh of ExecutiveBiz pointed out the connection, which is explained in a recent Frost & Sullivan press release.
While the $1.81 billion managed services market covers threat intelligence, detection and remediation, in the end, success still boils down to successful execution, according to Frost & Sullivan Network Security Industry Principal Frank Dickson. Managing risk with execution is a growing challenge, though, because more organizations are relying on cloud and mobile services.
“As with any service, the key to success lies in the execution,” Dickson states in the press release. “Value is not created the instant a sensor is placed on an endpoint or a new algorithm is applied to an advanced database tool, but in the months and years of work to integrate the data into the analytics by tenured security analysts that produce exceptional insights.”
What that means is that MSSPs that excel at the “time-consuming integration of data into the analytics that produce exceptional insights,” will offer the most robust and mature analytical insights.
Building the Foundation for the Industrial Internet of Things
Fitlinxx and other personal devices may be the hot ticket items this year, but when it comes to the Internet of Things, the real unheralded success story will probably be in manufacturing.
This so-called “smart manufacturing factory” won’t come without a serious re-architecting of enterprise systems around services and integration standards, notes a recent post on the blog Manufacturing Operations Management.
To be honest, I’m not entirely sure who writes this blog, other than a guy named “Conrad.” I tried to contact him via the comments section, but haven’t heard back yet.
Still, it’s pretty clear he knows his stuff just from reading it, because it’s a detailed look at what’s happening with protocols and within the industry to support data integration on the manufacturing floor — and across all the different types of equipment that manufacturers use.
If you’re interested in how to make the IoT a reality on the front line of manufacturing and operations, do yourself a favor and check out this post. You’ll find plenty of useful links.
Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter.