TechHub: Cyber in oil and gas, over 1,000 tech jobs created & more

ISA Director to oil & gas: “The time to act is now.”

Patrick Gouhin, Executive Director and CEO of the International Society of Automation (ISA) spoke at a Bloomberg Live conference in Texas on the future of cyber security in the oil and gas sector.

Patrick Gouhin cyber tech hub

Patrick Gouhin, ISA Executive Director and CEO. Image: LinkedIn

ISA is a nonprofit professional association that sets the standard for applying engineering and technology to improve management, safety and cyber security of automation and control systems.

Check out GrayMatter’s cyber services for operational technology.

The focus of his presence, according to Automation, an online industrial news website, was to urge industry executives to protect their facilities from cyber attacks.

He noted the increasing number of cyber attacks on industrial facilities, which are crucial to the economy and national security, and that there are effective standards available today.

“The time to act is now — not years in the future,” said Gouhin.

Supervisory control and data acquisition systems (SCADA) are used to monitor and control industrial networks, and are not designed to be resilient against cyber attacks.

The result? An attack can disable safe operations of these facilities, resulting in sometimes fatal consequences. Plant shutdowns, widespread blackouts, explosions, chemical leaks and more can result, according to Automation.

How much do you know, or not know, about your operational system? Take the industrial cyber security challenge to find out your knowledge level based on your score:

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New deal to add over 1,000 autonomous tech jobs within five years

General Motors announced plans to invest in autonomous vehicle technology startup Cruise Automation, with plans to double their current research and development facility and add 1,100 jobs over five years.

Currently Cruise is listed on Glassdoor.com as having under 200 employees, the deal increasing the company by 550 percent.

“As autonomous car technology matures, our company’s talent needs will continue to increase,” said Kyle Vogt, CEO of Cruise Automation.

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GM CEO Mary Barra with autonomous Chevy Bolt in 2016. Image: General Motors

Cruise and GM engineers are testing more than 50 Chevrolet Bolt EVs, which are built at the GM plant in Metro Detroit, Mich., with self-driving technology in San Francisco, Scottsdale and Metro Detroit, according to Industry Week.

Let’s talk ROI: Business and the Industrial Internet of Things

The momentum of the Industrial Internet of Things (IIoT) is undeniable. The benefits are among real-time connectivity and sensors, allowing for access to the data you want when you want it.

Yet many executives are still hesitant when implementing IIoT technology. The cautious attitude is due to the complexity of data architectures and massive enterprise-wide investments that require extensive engineering with long-term commitment, according to Industry Week.

This leaves them lost on measuring the value they’re receiving from their investment, and second-guessing whether they’re investing in the right approach for their company.

The answer? Finding a company that will work with customers to help find finite and scaled options to lower the risk of adopting to the new technology, yet still reap the benefits of the IIoT.

By integrating to IIoT platforms, it empowers plant operators to leverage their data and technologies to improve reliability, safety, energy management and overall operation performance for a price and level that works on an individual as-need basis.

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TechHub: Digital Disruption, IoT Expanding Digital Footprints and More

Digital Disruption Transcending Industry Borders

With the first quarter of 2017 coming to a close, it’s clear that the exponential growth within the technology industry is not slowing down.

25,000 new information-related jobs were created in February this year alone, according to Forbes.

As this tech push continues, we’re seeing more and more of the Digital Twin emerge as physical and digital worlds blend together.

The Digital Twin is the computerized companion of physical assets, using data sensors to show real-time data analytics.

The adoption of this trend is becoming increasingly popular as companies realize the countless benefits that the Industrial Internet of Things provides, and Augmented Reality and Artificial Intelligence become mainstream.

The biggest mistake companies are making right now is assuming these technologies won’t influence their business or impact their industry.

Industry 4.0 is real, and it’s here.

Smart technology is becoming integrated into every facet of life, resulting in customers having the ability to buy anything, anytime, anywhere.

“The convergence of cloud, mobile, social and data have ushered in a new wave of business models that will present unique challenges for various industries,” said Bob Weiler in Forbes.

With this new technology comes new challenges and questions emerging for industry leaders.

To stay ahead of the competition— and win— organizations will need partners who can provide a new level of knowledge and experience within the industry, according to Forbes.

Rethinking business models within critical industry operations is necessary to maximize performance.

The pace of change is accelerating fast. Organizations need to jump on board and embrace emerging digital technologies.

To learn the first three questions to ask in your digital transformation, join our webinar on Thursday, April 6, at 2:30 PM EST: Transform Your Operation: Vision Before Action.

Gray Matter Director of Professional Services John Benitz will demystify the beginning of the digital journey for you using his expertise on various transformations like the GE Brilliant Manufacturing process.

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Digital Transformation: Solving Big Manufacturing Problems

The top problems manufacturers are struggling with are visibility into operations, sharing information across one or multiple plants and allowing the right people to access the necessary data.

The solution? Digital transformation of plant operations.

“Digitizing production processes is more about running an efficient business than it is about jumping onto the next technology bandwagon,” said Industry Week.

Automating processes and storing big data on the cloud allows for a single connected platform with production visibility. It allows for a single-set of accurate data and increases the control plant operators need, according to Industry Week.

Instead of having information documented on manual paper processes like Excel spreadsheets, it can be accessed in real-time across one or multiple plants.

Access to product information, inventory, quality data and more increases the productivity and decreases downtime throughout the plant.

Automating the plant is also automating the communication, in turn freeing up people and resources. Instead of having to track down the necessary information and data, workers have instant access to it at a moment’s notice.

Going paperless and automating processes is a critical step within the industry, and lays the groundwork for future innovations.

Gray Matter has a new solution to help transform manual data entry processes into digital insights for manufacturers, utilities and energy companies.

Mobility@Work digitizes information that would have been buried in stacks of paper and puts data in a format that can be used for big picture analysis.

Hauling manifests, inspections, scheduling, incidents, inventory and time sheets are all transformed from piles on someone’s desk to an easy to read digital presentation.

“There are a lot of correlations you can make if you have the data working for you instead of in a stack of paper.” – Kemell Kassim, Gray Matter VP

Download the free white paper to learn how Gray Matter solved the manual data entry problem and helped save a leading energy company nearly $1 million in just the first year.

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IoT Devices Expanding Digital Footprints & Vulnerabilities

Security Week defines IoT devices as convenient.

They allow us to have access to data remotely and process it faster than ever.

However, with the convenience comes risk, and most people aren’t locking down their systems like they should be.

There are more avenues now than ever for cybercriminals to breach systems as more devices are connected and the digital footprint of plants are expanded.

The reality of IoT hacks is eminent. Recent research highlights how PLC controllers can be hacked and potentially taint water supply, according to Security Week. Not enough devices are accounted for, and too much personal and business data is intermingled.

The top recommendations to fix this are to get a clear policy in place, designate accountability and segment your network.

By having clear rules, placing risk and responsibility on people or teams and designating sections of your network help block the threat of cybercriminals. It makes finding an easy path into the network nonexistent.

IoT devices have a lot to offer in the world of operational technology and plant management, the risk just needs to be mitigated and vulnerabilities need to be tracked.

Gray Matter offers a vulnerability assessment for OT networks that creates a security baseline for each asset with an IP address.

In a recent interview with ARC Advisory Group, Gray Matter VP Kemell Kassim detailed recent cyber initiatives and ROI case studies.

Download the Q&A Here

CIO Survey Reveals Challenges, Opportunities and Potential of Industrial Big Data

Guest post by Jeremiah Stone, GM of Asset Performance Management at GE Digital. 

Bit Stew Systems recently commissioned a survey by IDG Research of senior IT executives to better understand how organizations are being impacted by the Industrial Internet of Things (IIoT) – the steps being taken to prepare for it, the potential benefits the IIoT offers, and the challenges encountered along the way.

Jeremiah Stone, General Manager of Asset Performance Management, at GE Digital, shares his insights on how the research findings match up with his experience at GE.

Industrial companies are in the midst of an exciting and transformational digital journey. At the heart of this transformation is the power of real-time and predictive data analytics to unlock new sources of value. However, challenges of big data, unique to the Industrial world, and the threat of digital disruption and changing workforce dynamics are real.

In order to maximize the fast-moving technology wave of the Industrial Internet, companies need to think strategically about the foundational elements of their data architecture, starting with industrial data management.

Abundant Data by Itself Solves Nothing
Despite the promise of big data, industrial enterprises are struggling to maximize its value. Why? Abundant data by itself solves nothing. Its unstructured nature, sheer volume, and variety exceed human capacity and traditional tools to organize it efficiently and at a cost which supports return on investment requirements. Inherent challenges tied to evolution and integration of industrial information and operational technology, make it difficult to glean intelligence from operational data, compromising projects underway and promise for further investment and value.

Research Confirms Data Integration is Slowing IIoT Adoption
We have seen first-hand, how data integration has challenged IT and OT teams for decades. The advent of IIoT adoption is compounding the problem. The insights from the IDG survey match up well with our experience. Senior IT executives are echoing the sentiment that data integration is the #1 barrier inhibiting IIoT adoption in their organizations. 64% of senior IT executives surveyed said that integrating data from disparate sources/formats and extracting business value from that data is the single biggest challenge of big data. As we go forward, driving technology advances and best practices to integrate disparate data sets is critical.

Lack of Preparedness will Cost your Business
According to the survey, senior IT executives are saying the biggest risk of not having an IIoT strategy in place is losing valuable data insights which can significantly cost their business. 87% state the most concerning risks of not have a data management strategy is they will be overwhelmed by the volume and veracity of data being generated, and they will lose valuable business insights as a result. In addition, 33% say they are afraid that businesses that don’t adopt a data management strategy will become marginalized, obsolete or disappear.

Finding a Better Way: Maximizing Value from Machines and Enterprise Data
At GE, we are experiencing first-hand a better way—a better way to manage industrial big data that triggers insights. We are in the early stages of a long journey
of discovery and invention, taking a longer-term view to strategic data management and its technologies that translate to business advantage. Our businesses, customers, and partners are committing their business success by transforming to become data-driven businesses. At GE Digital, we are investing in our capabilities and the ecosystem to deliver the right solution to help them get there.

To extract meaning and value from industrial data, new systems are required to handle the challenges posed by the volume, velocity and variety of these data sets. Many industrial companies have already started their digital journeys towards Industrial Internet maturity. Technologies including automated integration and empirical data model management, machine learning and physics-based analytics, that we have been deploying for our customers, are
now seeing double-digit performance gains across the following sectors: power generation, oil and gas, transportation and mining.

Learn More About This Topic

IDG Research White Paper | Download the in-depth report here.

This blog post originally appeared on Bit Stew Systems’ blog page, Bit View. 

Solving the Data Integration Problem with Bit Stew Systems

This guest blog post by Mike Varney originally appeared on Bit Stew Systems’ blog page, Bit View. 

Data integration is proving to be the Achilles heel of the Industrial Internet of Things (IIoT) and is blocking progress on
the transformations and ROI that industrial enterprises had originally envisioned.

Typical Big Data analytics projects that employ traditional ETL or Business Intelligence tools often falter under the complexity and scale of industrial environments. The rigid architecture and manual process associated with these solutions make them less than ideal for an industrial customer.

So why are so many industrial customers still using these clunky, brittle, and slow solutions?

ETL: Compounding Your Data Problem?
ETL or Extract, Transform, and Load is a traditional IT methodology whereby data systems architects tasked with Machine Intelligenceproviding data intelligence from multiple systems will first extract the data and place it all into a common location, then apply transformations to normalize or cleanse the data and then place it back in this common container for analysis. It may not seem laborious to the untrained eye but ask any data wrangler, enterprise architect, or IT manager and they will tell you that ETL can take several professionals months.

So why do it? ETL is attractive to IT departments because it usually leverages existing software investments and does not require teams to come up to speed on any new technology. In fact, it has been a tried and true method for decades.

IIoT Amplifies the Data Integration Challenge
Those who opt for traditional ETL are forgetting that the Industrial IoT is set to connect billions of more devices to the Internet by 2020. That explosion of data will most certainly be too rapid, and too large of a change for traditional systems to handle.

The risk for those who lag behind the curve on Industrial IoT is that they will cease to be competitive in the global industrial markets. Almost all industries will be affected by this change, from oil and gas to manufacturing and all those in between.

The technologies behind IIoT have brought significant advancements to industries such as Manufacturing, Transportation, Oil & Gas, Aviation, Energy, Automotive and others.  These technologies have allowed industry to remotely monitor and control assets to optimize production and improve yields.

However, these same technologies have exacerbated a long standing data integration problem by massively increasing the volume, velocity and diversity of data required by the business.

A New Way of ThinkingMachine Intelligence
Solving the data integration challenge requires a new way of thinking and traditional data architectures must be reimagined to support the rapid proliferation of data from an exponentially expanding set of data types. So what’s the solution? The key to solving the data integration challenge is semantics.

Bit Stew’s integration technology is designed to rapidly ingest and integrate data to provide a semantic understanding of information across disparate systems. Deeper analytics can then be applied intelligently through analysis methods and workbenches.

Download the infographic to get a deeper understanding of the steps required to create a semantic model.

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