CHOOSING AN SD-WAN FOR GLOBAL ENTERPRISE APPLICATIONS

"Good-enough" IT architecture for remote workers isn't good enough anymore. To support a permanently hybrid workforce, enterprise leaders need to ask themselves tough questions: Do you simply add "must have good broadband" to job listings, or can IT departments redesign their network architecture to accommodate talent wherever it resides? Are you using employee monitoring and productivity tools responsibly, or are they violating privacy? In this Interop event, learn the latest in hybrid work trends including new technologies to better observe, support and defend your users, wherever they choose to work.

Companies across industries face new challenges connecting with empowered consumers. Customers have been completely altering their shopping habits in recent months like never before. With shops closed or limited entry, purchasing has shifted to online, loyalty has shifted by industry and brand, safety is paramount, and all of it varies by geography. Compounding the challenges, consumers expect more information that is tailored to them about what to buy and where the best deals are. In this webinar we take a look at how injecting machine learning into your existing business intelligence solutions and processes can fundamentally change how you connect with customers, and ultimately improve business results.

Looking for a way to advance to Industry 4.0 while obtaining a competitive edge AND driving new revenue though the Industrial Internet of Things (IIoT)? IIoT is driving disruptive transformation by breaking down product silos, increasing engineering efficiency, enabling cross-functional innovation, and creating new value-added connected services. “Eighty percent of the industrial segment believes that the IoT will be transformative and disruptive, but 90% feel they are unprepared for these changes”, according to Derek O’Halloran, head of information technology and electronics industries, and member of the leadership team, at the World Economic Forum.

Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success is the deployment and management of models in production requiring new technology and practices. This new area is called Machine Learning Operations or MLOps.