See how AI is upping the ante in security operations. Plus, FedEx using more than just scan data to improve their flow of goods. And, synthetic data providing a great option when needed data doesn’t exist. Finally, SaaS-based cloud approach saves enterprises substantial time and money and is becoming a more realistic approach for businesses looking for availability, functionality, and flexibility.
By Steve Lasky, contributing writer for Securityinfowatch.com
The paradigm shift in physical security from a reactionary and defensive proposition to a more proactive stance has characterized the migration of advanced analytics into almost every platform. Security end-user demanding systems that are faster and more intelligent, and at the same time cost-efficient and better suited for integrated solutions, are looking for more than technology that detects and deters. They now require systems that can digest vast amounts of data, then process autonomously monitored responses at lightning speeds. Upping the preemptive ante is a crucial step in the growth of intelligent physical security systems. And it is currently moving beyond the ubiquitous use of video surveillance analytics to other sensory devices at the edge and controlling access into and across the interior of a facility.
By Steve Banker, contributing writer for Forbes.com
A network effects business model allows a company to gain more value as more companies use its products or services. The value of the offering rapidly increases because each additional user increases the value of the network. Today, we mainly think of digital companies like Google GOOG +0.2% and Twitter in this category. Google and Twitter mainly monetize the data through targeted advertising. The value of the data captured by Google and Twitter has made them the darlings of Wall Street.
By Isaac Sacolick, contributing writer for Infoworld.com
Devops teams aim to increase deployment frequency, reduce the number of defects found in production, and improve the reliability of everything from microservices and customer-facing applications to employee workflows and business process automations.
By Aishwarya Banik, contributing writer for Analyticinsights.net
The term “machine learning” refers to a sort of Artificial Intelligence (AI) that allows computers to learn without having to be explicitly programmed. Machine learning, to put it another way, is concerned with the creation of computer programmes that can train itself to change or execute predictive models which learn from fresh and innovative data to anticipate future behaviours, events, and trends. Meanwhile, cognitive systems, a less evolved kind of AI, analyse and categorise unstructured data using predictive modelling and logical reasoning.
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