Today, businesses are entering into a new era ruled by data. AI, specifically, is gradually evolving into a key driver that shapes day-to- day business processes and Business Intelligence decision-making.

Thanks to advances in cognitive computing and AI, companies can now use sophisticated algorithms to gain insights into consumer behavior, use the real-time insights to identify trends and make informed decisions that give them an edge over their competitors.


The proliferation of new big data sources, including smartphones, tablets and Internet of Things (IoT) devices, means business no longer wish to be weighed down by huge chunks of static reports generated by BI software systems. They need more actionable insights.

This is inspiring a move away from reactive analytics to proactive analytics that offer alerts and real-time insights. These analytics allow the companies to make better use of their operational data while it’s fresh and actionable.

Over the years, BI software has evolved into three essential areas:

  • Descriptive analytics – The most straightforward BI system that summarizes data and informs what happened. It does precisely what the name implies: description. It summarizes raw data and breaks it down into something that can be interpreted by humans. Descriptive analytics enables companies to understand past behaviors and learn how it can influence future outcomes.
  • Predictive analytics – This “predicts” the future. Predictive analytics enables companies to have future insights. Although no statistical algorithm can give 100% prediction, organizations are using these analytics to forecast future events. This system relies on “best guesses” since its foundation is based on probabilities.
  • Prescriptive analytics – A relatively new but robust field that enables users to prescribe various possible actions and advise accordingly towards viable solutions. Prescriptive analytics is all about providing advice. These AI-powered analytics not only predict what will happen but also explain why it will happen.

The enormous progression in analytics and BI tools indicates that businesses are requiring more mature decision-making. Recent business digitization aims at getting to prescriptive level of analytics.


AI has evolved into that “can’t do without” technology in the modern business landscape. Small to large enterprises are leveraging this technology to improve the efficiency of business processes and deliver smarter, more specialized customer experiences. The question is, how is artificial intelligence changing the scenes of today’s business environment?

  • It’s rapidly transforming different industries. AI is quickly changing heavily regulated industries like healthcare, financial services, life sciences and the trading industry. For instance, in medicine, AI is taking the roles of clinical assistant to help physicians make faster and reliable diagnoses. It’s also accelerating the creation and discovery of new drugs and medication.

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Article Credit: Dataconomy

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Under 1% of data could cost enterprises 4% of annual turnover in May 2018, says GDPR

Metadata discovery software vendor Silwood Technology has conducted research into five of the largest and most widely used application packages to understand the scale of the challenge encountered by their customers when locating personal data for GDPR compliance.

It is vital to perform this ‘discovery’ work for any GDPR project. Without a clear understanding of where personal data is located in each of the systems in an enterprise, it will not be a straightforward task to carry out any of the steps to reach GDPR compliance.

The research reveals that the task facing organizations in the coming few months is significant. In SAP alone there are over 900,000 fields that may (or may not) contain personal information that require data discovery and risk assessment. The size and complexity of the databases mean that businesses that are not well-advanced in data discovery or are undertaking manual discovery processes may not be ready on time for GDPR.

Using Safyr, Silwood Technology’s metadata discovery software, the research team selected the top five application packages based on customer base and size – SAP, JD Edwards, Microsoft Dynamics AX 2012, Siebel and Oracle E-Business Suite. The terms Date of Birth and Social Security Number were selected for test purposes and searches performed to see how often they appeared.

The researchers using Safyr were able to conduct these searches across whole systems in just a few minutes.

This is due to Safyr’s unique ability to retrieve metadata about each application from the application layer itself – including any customizations made by the customer. Safyr is designed specifically to make the discovery of metadata in ERP and CRM packages easy, fast and accurate.

Founder and Technical Director of Silwood Technology, Nick Porter, commented: “Whilst GDPR needs to be considered for any ‘system’ that potentially stores information about individuals (including paper-based systems), much of the data in a medium to large sized organization will be found in one or more of the major application packages from SAP, Oracle or Microsoft.

“With GDPR coming, those application packages that have been modified or customized will be the most difficult in which to locate personal data information. Whilst SAP is the biggest of the ERP vendors (exact figures are hard to come by, but it is generally accepted that there are around 30,000 SAP ERP customers), Oracle and Microsoft also have a significant presence.”

What is Personal Data in GDPR terms?

The ‘Data’ in the General Data Protection Regulation is what the guidance calls Personal Data. For example, if a living individual can be identified from any data being processed, it is covered by GDPR. This might be a single piece of information, like a Social Security Number, or several pieces of data that can be combined to identify someone (e.g. Name and Date of Birth).

Exactly what constitutes Personal Data will vary from customer to customer, depending on the industry type. For example, in the healthcare sector, Patient Number would be a means to identify a person, but this would be irrelevant in, say, manufacturing.

Personal Data in five leading application packages

Silwood Technology used its Safyr metadata discovery software to conduct a deep dive into five of the largest and most widely used ERP and CRM application packages.

When looking at the five leading application packages, Silwood Technology’s focus was to locate the personal data fields in their databases. Databases are composed of tables, which for those unfamiliar with the relational database model, are like files in a physical storage system. Each table has a number of columns – like the fields on a physical form and are referred to as fields in this analysis.

Safyr is available as a free trial here:

If, for example, Date of Birth appears 100 times in the tables, each of the 100 occurrences needs to be reviewed to determine whether it constitutes personal data from the enterprise’s (and hence a GDPR) perspective. In another package, the fact that the Date of Birth appears only ten times might sound ‘better’ – but only if there is an efficient way to find the ten mentions amid the thousands of other fields in the system.

The team wanted to research the frequency with which certain personal data categories occurred in the chosen applications.

Several instances of each package were examined and the statistics presented give an indication of how many occurrences of each field will be found in a typical system.

Silwood Technology selected Date of Birth and Social Security Number as examples for test purposes. However these packages, and others like them, have a host of other Personal Data fields that would also need to be considered in any GDPR compliance programme. The results for each package are below.


SAP is by far the largest ERP application package in terms of its market presence, size of customer base, breadth of functionality and the sheer number of tables in its database.

According to Panorama Consulting Solutions*, SAP has over 20% of the ERP market share.

Silwood found that:

  • There are typically in excess of 90,000 tables in a SAP system and over 900,000 fields
  • Social Security Number, or its equivalent appears in over 900 tables
  • Date of Birth appears in over 80 tables.

Nick Porter said: “Less than 1% of a typical SAP system contains the personal data that could cause GDPR breaches that cost your organization up to 4% of its annual turnover.

“It’s often medium-sized businesses that attempt manual data discovery. On average, an SAP implementation will take more than 20 times longer to locate personal data using traditional approaches, compared with an automated solution.”

JD Edwards

JD Edwards offers ERP functionality that at the superficial level provides similar features to SAP but at a much lower cost of ownership. Like SAP, JD Edwards’ strengths are in manufacturing. JD Edwards is one of a number of packages offered by Oracle that includes PeopleSoft, Siebel and Oracle EBS. Overall, Oracle has nearly 14% market share, second only to SAP*.

JD Edwards does not have the depth of industry-specific applications offered by SAP, and is much smaller than SAP, in terms of the metadata footprint, but still very challenging.

Silwood found that:

  • There are approximately 5,000 tables and 140,000 fields
  • Social Security Number (JDE calls it Tax ID) appears in over 170 tables
  • Date of Birth in over 210 tables.

Microsoft Dynamics AX 2012

Microsoft Dynamics AX 2012 is an ERP system suitable for midsize to large enterprises. The solution has particular strengths in manufacturing and distribution. There are a number of differing packages that fall under the ‘Dynamics’ umbrella, and together these give Microsoft nearly 10% market share*, putting them third place in Panorama Consulting’s ranking.

Silwood found that:

  • There are approximately 7,000 tables and 100,000 fields
  • Social Security Number (Microsoft Dynamics calls it Tax Code) is located in over 150 tables
  • Date of Birth is in approximately 10 tables.


Whilst Siebel has been largely overtaken by Salesforce as the leading CRM package, it retains a large user base.

Silwood found that:

  • There are around 5,000 tables in a typical Siebel system and approximately 170,000 fields
  • Social Security Number was found in 14 tables
  • Date of Birth in over 6 tables.

Being a CRM system, Siebel and similar systems will be a prime target for GDPR.

Oracle E-Business Suite

Oracle E-Business Suite is another of Oracle’s package offerings with strong functionality across the range of ERP applications.

Silwood found that:

  • There are around 22,000 tables and approximately 570,000 fields
  • Social Security Number was found in 5 tables
  • Date of Birth in over 40 tables.


The task of locating Personal Data is part of the ‘Information Audit’ phase of a GDPR project. This will inform other steps in the process of becoming compliant, such as delivering Data Subjects’ Rights for Rectification, Deletion and Access.

Unfortunately, no ERP or CRM application specialist will be familiar with all the tables in their databases. And the Social Security Number and Date of Birth are just two types of data – there are tens if not hundreds that need to be located and recorded. Therefore some form of automation is required to make the task achievable.

Nick Porter concluded: “The GDPR becomes enforceable across the EU in May 2018, and not since Y2K has there been so much confusion and hype around a single business issue. Every software company and consulting firm that even remotely plays in the data governance space is jumping onto the GDPR bandwagon. The reality is that there is no one GDPR ‘solution’ and any company saying they have one is probably overplaying their capabilities – unless of course throwing bodies at the task is considered to be a solution.

“The scale of the issue means that businesses that are not well-advanced in data discovery or are undertaking manual discovery processes will struggle to be ready on time for GDPR.”

To assist SAP customers who are trying to find personal data in their ERP systems, Silwood have released a Safyr GDPR Starter Pack. This will accelerate the information audit process for them. We are also planning further Starter Packs for other applications in the near future

* Panorama Consulting Solutions – 2017 Top 10 ERP System Ranking.

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Manufacturing businesses report high levels of fraud, cyber and security incidents in 2017

Fraud, cyber, and security risks continue to reach high levels in the manufacturing sector, according to senior corporate executives surveyed worldwide for the 2017/18 Kroll Annual Global Fraud & Risk Report.

The proportion of executives reporting that their companies fell victim to at least one instance of fraud over the past 12 months was 86%, two percentage points higher than the global average across all industry sectors (84%).

An even greater percentage of executives from the manufacturing sector (88%) said their companies had experienced a cyber incident or information theft, loss, or attack over the past 12 months. Just over seven in 10 respondents (72%) reported the occurrence of at least one security incident during the past year, two percentage points above the global average.

The Kroll Report reveals that respondents in the manufacturing sector are experiencing a heightened sense of vulnerability to fraud, cyber, and security risks, with information-related risks now being the area of greatest concern. As criminals and other threat actors continue to find new ways to monetize confidential data, including personal data, data assets are becoming increasingly valuable and attractive targets.

Confidential information subject to increasing threats

Information theft, loss, or attack was again the most prevalent type of fraud experienced in the manufacturing sector, cited by 33% of respondents, up 3 percentage points from the previous year. Corruption and bribery was second on the list, reported by 28% of executives, more than twice the reported incidence in last year’s survey (12%).

More respondents from the manufacturing sector (88%) reported cyber incidents compared to the global figure of 86%. In the year when major viruses such as WannaCry and Petya hit across the world, nearly four in 10 (38%) executives surveyed said their companies had been impacted by a virus or worm attack. A quarter (26%) said they had suffered an email-based phishing attack and the same proportion suffered a data breach.

Physical theft or loss of intellectual property (IP) was by far the most prevalent type of security incident. Of those executives in the manufacturing sector whose company experienced a security incident this past year, 45% said their organizations fell victim to IP theft or loss.

Top three types of incidents reported by survey respondents (by category)

  Fraud Cyber Security
1. Information theft, loss, or attack (33%) Virus/worm attack (38%) Physical theft or loss of intellectual property (45%)
2. Corruption and bribery (28%) Data breach resulting in loss of customer or employee data, IP/trade secrets/R&D (26%) Environmental risk (including damage caused by natural disasters such as hurricanes, tornadoes, floods, earthquakes, etc.) (24%)
3. Management conflict of interest (26%) Email-based phishing attack (26%) Workplace violence (19%)

Jason Smolanoff, Senior Managing Director and Global Cyber Security Practice Leader for Kroll, explained: “In a digitised world with growing levels of data creation, collection, and reliance for businesses, information assets have become increasingly valuable and exposed to threats. Exacerbating the challenge of safeguarding data is that criminals and other threat actors are continually developing new ways to monetise confidential information, including personal data.
“People instinctively think about data being targeted by cyber attacks, but not all threats to information are confined to the digital realm. There is a convergence between physical and digital threats, with issues arising from equipment with sensitive data being stolen or lost, for example, or employees with access to highly sensitive information accidentally or intentionally causing a breach.”

Costly and wide-ranging repercussions

In addition to reporting extremely high incidence levels, respondents from the manufacturing sector indicated that the repercussions of fraud, cyber, and security events were costly and wide-ranging, affecting employees, customers, as well as the organisation’s reputation and bottom line.
Employee privacy, safety, or morale was negatively affected by incidents according to 76% of respondents whose companies had experienced fraud, 86% of those that reported a cyber incident, and 76% of executives whose companies endured a security event.
Approximately two thirds of respondents stated that customers had been negatively impacted by all three risk factors – 66% by a fraud incident, 63% by a cyber incident, and 59% by a security incident. A similar proportion said that the impacted company’s reputation had suffered due to a fraud (66%), cyber (68%), or security (69%) incident.
Businesses suffered significant economic damage from fraud, with nearly one in five respondents (18%) reporting losses of 7% or more of company revenues. No respondents from the manufacturing sector reported this magnitude of financial impact in last year’s survey.

Executives feeling increasingly vulnerable to risks

The Kroll Report further reveals mounting concerns among surveyed executives about their companies’ potential exposure to fraud, cyber, and security risks. In particular, information-related risks overwhelmingly represent the top worries for respondents across all three risk categories.
More than six in 10 (62%) respondents from the manufacturing sector believe their companies are highly or somewhat vulnerable to information theft, loss, or attack, 5 percentage points higher than the global average.
With reported cyber incidents at an all-time high and perpetrators seeming to develop new methods of attack virtually every day, at least half of all executives surveyed are apprehensive about every type of cyber incident identified in the survey – with 57% especially wary of data deletion.
The proportion of respondents from the sector who said they feel highly or somewhat vulnerable to physical security threats was also substantial. More than half (53%) of respondents stated their companies could be particularly prone to physical theft or loss of IP, the greatest single concern.

Culprits inside and outside

Insiders and ex-employees continue to pose the greatest fraud threat to companies in the manufacturing sector. Respondents revealed that fraud incidents are often inside jobs perpetrated by one or more of the following: junior employees (42%), ex-employees (34%), or vendors/suppliers (30).
Random perpetrators were the main culprits of cyber (41%) and security (31%) incidents experienced by executives in the manufacturing sector.

Imperative to mitigate risks

Nearly all anti-fraud measures mentioned in the survey were widely adopted by over 70% of respondents in the manufacturing sector, with financial controls the most widely implemented anti-fraud measure at 84%.
Cyber security is rapidly becoming a board governance mandate as the anticipated likelihood of an incident grows, compounded by increasing regulatory pressures and the costly reputational risks associated with data privacy and data loss events. 49% of respondents currently involve the board of directors in the formulation of cyber security policies and procedures, and another 39% plan to do so in the next 12 months.
A large proportion of respondents have adopted security risk mitigation measures, but given the high incidence and feelings of vulnerability around theft/loss of IP, it was surprising to see that only 73% of respondents have a plan for securing intellectual property. However, almost a quarter (21%) of respondents plan to implement these measures over the next 12 months.
Kroll CEO David Fontaine commented: “Senior executives are becoming acutely aware that threats to their organisations can arise at any time and originate from any place.  Insiders and ex-employees continue to pose a significant threat and have, together with external criminals and threat actors, more tools at their disposal than ever before with which to target and exploit companies.
“In the face of these mounting threats, organisations seeking to manage and mitigate the possibility of loss must take a holistic approach to enterprise risk management and implement diverse and layered measures that can enhance their ability to anticipate, detect, and respond to threats rooted not only in human error or intentional misconduct, but also in technological or internal control gaps.”

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Humans must ‘connect brains with AI’ or face EXTINCTION in ‘robot utopia’

robot utopia

robot utopia

AI engineer, Dr Ian Pearson, says technology is developing so rapidly we are likely to see “superhuman AI” in future.

He believes the technology will drastically surpass the ability of the human mind because it will take the form of “superhuman conscious AI”, with “emotions and agendas”.

But the ex-rocket scientist warns these robots risk wiping out normal humans because we cannot compete.

The only way to avoid this, the futurologist says, is to link our brains to AI so that we have access to the same pool of intelligence as future robots.

Writing for his tech blog, Futurizon, Dr Pearson said: “The technology potential for this is vast and very exciting, nothing less than a genuine techno-utopia if we use the technologies wisely.

“But optimum potential doesn’t automatically become reality, and achieving a good outcome is unlikely if many barriers are put in its way.”

He added: “This AI development trend will take us to superhuman AI, and it will be able to accelerate development of its own descendants to vastly superhuman AI, fully conscious, with emotions, and its own agendas.

“That will need humans to protect against being wiped out by superhuman AI.

“The only three ways we could do that are to either redesign the brain biologically to be far smarter, essentially impossible in the time-frame, to design ways to link our brains to machines, so that we have direct access to the same intelligence as the AIs.

“So a gulf doesn’t appear and we can remain relatively safe, or pray for super-smart aliens to come to our help, not the best prospect.

“Therefore we will have no choice but to make direct brain links to super-smart AI. Otherwise we risk extinction. It is that simple.”

Dr Pearson, 57, adds that he believes the technology that will enable humans to connect their brains to AI in 2045.

He added: “Best guesses for time-frame fall in the 2045-2050 range for a full working link that not only relays signals between your organic bran and an IT replica, but by doing so essentially makes external IT just another part of your brain.”

In an exclusive interview, Dr Pearson previously told Daily Star Online that he believes football robots will be better than Barcelona star Lionel Messi, 30, by the year 2045.

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Article Credit: Daily Star

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Robots versus procrastination

Business owners are always trying to increase productivity in the workplace. They can introduce exercise breaks, have standing meetings and organise team-building days. However, in the manufacturing sector, these initiatives are unlikely to have an impact. Here, Jonathan Wilkins, marketing director at obsolete industrial parts supplier, EU Automation, explains how automation improves human productivity.

In the manufacturing sector, introducing automation to the assembly line is one way facilities managers can increase production.

Historically, humans have had a strained relationship with technology, fearing it will take their jobs. However, increased automation can do more than take over jobs, it also improves human productivity. This can be by completing the dangerous tasks that humans do or streamlining processes to make human work easier.

Augmented reality

Augmented reality (AR) helps upskill employees by providing necessary information at the touch of a button. For example, data on wearable technology can instruct an employee on how to repair a machine and inform other workers about the maintenance work.

AI and machine learning

Artificial intelligence (AI) can carry out many tasks in consumer applications, from playing chess to taking dinner orders. In industrial applications, AI assists manufacturers with decision making, in everything from maintenance to business strategy.

Some argue that AI will take away human involvement in projects. However, AI is there to support human decisions rather than make the decisions for them. AI will be able to show all of the possible decisions faster than a human to ensure that every possible route is considered.

Cloud computing

It is difficult to keep track of documents, calendars and everything else on computers, especially when there are multiple devices, other people’s computers and software updates to contend with.

Cloud computing allows an entire workforce access to the same files. This means that multiple versions of documents don’t have to be created, so everyone knows what is going on and has the ability to collaborate on that work.

As more businesses open international offices, cloud computing allows international collaboration, as one person in Singapore and one in the UK can edit the same document from their own desks. Cloud computing also controls software updates to ensure all technology is up to date, giving human workers time to produce more innovative services and have a cost-effective way of having the latest technology.

With careful consideration, facilities managers can invest in automation to help human workers become more productive. Away days and office activities can be great for team building. However, the best method for drastically increasing productivity in manufacturing is to streamline processes using automation alongside humans.

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A Scientist’s View on Why the AI Apocalypse Isn’t the End of the World

the AI

the AI

Artificial intelligence is often portrayed by mainstream media as a “black-box” technology, where we pose a problem, feed a raw set of data into an algorithm system and let it figure out a solution to by itself—and, over time, as the system learns from its own previous experiences, it gets better at problem-solving.

But no one knows what exactly happens between these steps. 

However, that doesn’t stop Silicon Valley investors from pouring venture capital into startups that build business upon artificial intelligence and vow to change the world. According to CB Insights data, between 2012 and 2016, venture capital funding in AI startups increased more than eightfold.

As the AI buzz gets louderworries around the so-called “AI apocalypse” have emerged.

People fear that robots will replace humans in most functions in our society. AI robots are already serving as supermarket cashiers, baristas, stock advisors and even pets. A McKinsey study projects that, by 2030, 800 million human jobs will be replaced by robots.

However, inside the AI academia, scientists are seeing a slightly different picture.

“Machines still have a long way to go to replace humans,” Kyunghyun Cho, a scientist of Facebook AI research and a data science professor at New York University, told Observer in a recent interview. 

Cho is a rising star in machine translation, an subfield of computational linguistics that has seen major breakthroughs in recent years thanks to the application of AI. Cho was named on Bloomberg’s list of “people to watch in 2018.” Geoffrey Hinton, a computer science professor at the University of Toronto, who is regarded as “the Godfather of AI,” told Bloomberg that Cho’s work had a huge impact on machine translation.

Machine translation aims to use softwares to translate text or speech from one language to another. Scientists have been working in this field for decades, but major progresses didn’t start taking place until the last five years, when large-scale neural networks began being applied to power the translation process. 

The technology is now widely used in everyday internet tools and home devices like Google Translate, Apple’s Siri and Amazon’s Alexa smart speakers.

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Article Credit: Observer

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Why even a moth’s brain is smarter than an AI

A neural network that simulates the way moths recognize odors also shows how they learn so much faster than machines.

 brain is smarter than an AI

brain is smarter than an AI

One of the curious features of the deep neural networks behind machine learning is that they are surprisingly different from the neural networks in biological systems. While there are similarities, some critical machine-learning mechanisms have no analogue in the natural world, where learning seems to occur in a different way.

These differences probably account for why machine-learning systems lag so far behind natural ones in some aspects of performance. Insects, for example, can recognize odors after just a handful of exposures. Machines, on the other hand, need huge training data sets to learn. Computer scientists hope that understanding more about natural forms of learning will help them close the gap.

Enter Charles Delahunt and colleagues at the University of Washington in Seattle, who have created an artificial neural network that mimics the structure and behavior of the olfactory learning system in Manduca sexta moths. They say their system provides some important insights into the way natural networks learn, with potential implications for machines.

First some background. The olfactory learning system in moths is relatively simple and well mapped by neuroscientists. It consists of five distinct networks that feed information forward from one to the next.

The first is a system of around 30,000 chemical receptors that detect odors and send a rather noisy set of signals to the next level, known as the antenna lobe. This contains about 60 units, known as glomeruli, that each focus on specific odors.

The antenna lobe then sends neural odor codes to the mushroom body, which contains some 4,000 kenyon cells and is thought to encode odors as memories.

Finally, the result is read out by a layer of extrinsic neurons, which number in the 10s. These interpret the signals from the mushroom body as actions, such as “fly upwind.”

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Article Credit: MIT Technology Review

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DEACOM’s Specialization Drives Miller Chemical & Fertilizer to Strengthen International Business

DEACOM, Inc., the developer of a comprehensive Enterprise Resource Planning (ERP) solution, has been selected by Miller Chemical & Fertilizer, LLC to help grow their international business. Currently serving more than 90 counties, the chemical company is maneuvering many unique challenges for documentation, regulation, and inventory requirements, yet their legacy ERP system is planned to discontinue later this year. By investing in DEACOM ERP, the process manufacturer will be able to capitalize on a long-term solution with the necessary functionality built specifically for its international business.

“In order to meet our aggressive growth plans over the next four years, we came to the conclusion that we could not continue to operate on an unsupported system,” said Tony Hartlaub, Vice President of Finance for Miller Chemical & Fertilizer. “Rather than embarking on a re-implementation of the generic, legacy system, we have decided to replace it with Deacom’s industry-specific ERP solution. This change will allow for more automated procedures that are designed to encourage scalability of our business over time.”

The ERP provider’s Kaizen development philosophy ensures that the software is constantly evolving alongside changing requirements and regulations. With the industry’s largest functional foundation tailored towards the specific needs of manufacturers and distributors, Deacom customers are able to leverage the most applicable functionality limiting their dependence on bolt-ons or customizations.

Using a single set of business logic, companies like Miller Chemical & Fertilizer can centralize all business operations and access critical data in real-time – meeting important international requirements. By automating document generation for CoA, GHS, and SDS forms, as well as foreign currency and tax requirements, the company can reallocate efforts to focus on strategies to expand the business.

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Petrosoft Partners With Saint Vincent College To Accelerate Growth And Help Students Meet Their Professional Goals

Petrosoft, a global provider of end-to-end retail solutions, announces it has partnered with Saint Vincent College, an innovative provider of higher learning and an SAP University Alliance member. The partnership helps to accelerate the growth of the company’s Petrosoft Enterprise powered by SAP Business One’s implementation and support team. Students enrolled in the Alex G. McKenna School at Saint Vincent College’s SAP Business One® program obtain real-world business experience by completing an internship with Petrosoft.

With Petrosoft’s technology, retailers obtain real-time information by automating the collection, distribution, and analysis of facility-level data from transactions, equipment, and sensors. Students will learn how these solutions can solve complex business problems through hardware, software, cloud-platforms, and ERP solutions. Students will also learn how the industry is being transformed by the Internet of Things (IoT).

The Alex G. McKenna School at Saint Vincent College certification in SAP Business One® helps students broaden their business understanding by providing real-work experience. As a member of the SAP University Alliance, Saint Vincent’s program offers students a combination of classroom training, hands-on experience, and an internship so they can be prepared to contribute their knowledge of and experience with this integrated management solution.

“We are impressed by the program offered by Saint Vincent College and the enthusiasm of its students. Petrosoft is proud to help these students gain experience with a product that we know will help to transform the retail industry,” said Sergei Gorloff, CEO and President of Petrosoft.

“The Alex G. McKenna School of Business, Economics and Government at Saint Vincent College is honored to add Petrosoft as another partner in conjunction with our 10-year participation in the SAP University Alliance program,” commented Robert A. Markley Jr., Carpenter Technology – Latrobe Specialty Metals Sponsored Lecturer in Business Administration. “We are excited to offer our students this excellent opportunity for internships which will likely lead to high-paying, full-time careers in the SAP ecosystem. It’s yet another win-win for our students!”

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Google’s new AI algorithm predicts heart disease by looking at your eyes

Experts say it could provide a simpler way to predict cardiovascular risk

 AI algorithm

AI algorithm

Scientists from Google and its health-tech subsidiary Verily have discovered a new way to assess a person’s risk of heart disease using machine learning. By analyzing scans of the back of a patient’s eye, the company’s software is able to accurately deduce data, including an individual’s age, blood pressure, and whether or not they smoke. This can then be used to predict their risk of suffering a major cardiac event — such as a heart attack — with roughly the same accuracy as current leading methods.

The algorithm potentially makes it quicker and easier for doctors to analyze a patient’s cardiovascular risk, as it doesn’t require a blood test. But, the method will need to be tested more thoroughly before it can be used in a clinical setting. A paper describing the work was published today in the Nature journal Biomedical Engineering, although the research was also shared before peer review last September.

Luke Oakden-Rayner, a medical researcher at the University of Adelaide who specializes in machine learning analysis, told The Verge that the work was solid, and shows how AI can help improve existing diagnostic tools. “They’re taking data that’s been captured for one clinical reason and getting more out of it than we currently do,” said Oakden-Rayner. “Rather than replacing doctors, it’s trying to extend what we can actually do.”

To train the algorithm, Google and Verily’s scientists used machine learning to analyze a medical dataset of nearly 300,000 patients. This information included eye scans as well as general medical data. As with all deep learning analysis, neural networks were then used to mine this information for patterns, learning to associate telltale signs in the eye scans with the metrics needed to predict cardiovascular risk (e.g., age and blood pressure).

Although the idea of looking at your eyes to judge the health of your heart sounds unusual, it draws from a body of established research. The rear interior wall of the eye (the fundus) is chock-full of blood vessels that reflect the body’s overall health. By studying their appearance with camera and microscope, doctors can infer things like an individual’s blood pressure, age, and whether or not they smoke, which are all important predictors of cardiovascular health.

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Article Credit: The Verge

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