R. Danes
Latest from R. Danes
Cloud microservices democratize cutting-edge communication tech
Unified communications software. It may sound like something reserved for giant organizations with thousands of dispersed personnel, but it’s not. It’s really just software to improve all types of communication in enterprises. And with cloud and microservice models, vendors are turning out approachable, affordable UC technology for everyone. Diane Smith (pictured), president and chief executive officer of ...
In the zone with new AI-enabled devices for collaboration clouds
Cloud-based enterprise communication technology extends users plenty of favors. Users no longer have to configure different components of collaboration tools themselves. They can now access ready-made, holistic, software as a service solutions. But users still need collaboration devices — new, improved, purpose-built ones. “At the end of the day, all of that collaboration cloud gets accessed through a ...
The best CX is good AX: Intelligence for contact-center ‘super agents’
It’s getting tougher for companies to secure customer loyalty. Online product reviews and easy-opt-out digital models let them research and switch brands in a few clicks. The business is on the line during the few minutes an agent spends talking to a customer. New enterprise-communication tech aims to end that all-important call on a happy note. ...
Jarvis on the job? An analyst’s enterprise-AI reality check
Enterprise technology has come a long way from the conference-call speaker phone. Workers increasingly want artificial intelligence and automation to complete tasks on their behalf. But can we really expect Jarvis from “Iron Man” to show up and do spreadsheets any time soon? “We do think that the enterprise will become more intelligent and that ...
Thanks for sharing: Should companies pool data for strong AI algorithms?
Does the future of accurate data analytics rest on companies learning to share? Selecting training data for algorithms raises tricky question about greater good versus competitive advantage. The market for advanced call-center software is a good place to work out the answers. No company’s data should go into an algorithm without its express permission, Jonathan Rosenberg ...
Marketers moonlighting as data scientists? Get real. Hire a data team
Some companies opt to run random big-data experiments in pockets of their organizations. Perhaps marketing will hire a person or two to help them analyze data on lead conversion. Maybe they will derive profitable insights; maybe they won’t. Companies serious about becoming agile, data-driven machines need a more organized, centralized approach. It begins with hiring ...
Alaska Airlines and others ‘tech out’ planes, apps and more to land flyers
Technology is taking to the skies. Airlines are staking new competitive territory with tech on and off planes. Data-driven applications, on-board Wi-Fi connectivity, and virtual reality are just some things they are offering to tech-savvy flyers. Alaska Airlines Inc. is among those looking to leverage technology to revolutionize flyers’ experiences. It merged about two years ago ...
WiDS Datathon mixes up data science with collaborative teams
If only a data set and some pre-packaged data-analytics software were all it takes to solve real-world problems. The reality is that tools require hands to ply them. And just like a comprehensive data set is better than a limited one, a comprehensive set of skills helps people design better solutions. “Looking at the problem ...
VIDEO EXCLUSIVE
In troubled times for media, the inspiring legacy of Computerworld founder Patrick McGovern
What would the history of information technology be without Patrick McGovern? Most readers may not know his name, but they likely have read a number of publications within his technology media empire, International Data Group Inc. Over several decades, it spawned 300 publications to form a constant fount of knowledge for thirsty techies and tech ...
VIDEO EXCLUSIVE
AI’s people problems: Pros tackle ethics and bias in data science
Two developments have ushered in this golden age of data analytics. One is the gargantuan, always-expanding volume of data available. The other is advanced new machine-learning and artificial-intelligence technology. One might think these two dogs could race to the finish by themselves. There is, however, another element needed in data science today. Without it, skewed ...