Experian CIO: IT Standardization Drives Agile
Consumer credit reporting company Experian's IT infrastructure and data storage is measured in petabytes, so standardizing on a technology stack has meant a lot of change and big rewards.
CompTIA Names Top 10 Emerging Technologies
New technologies keep on coming, but which are better to invest in now versus later? CompTIA's recently released a prioritized list of top 10 emerging technologies. We compared it with CompTIA's latest State of the Channel Report.
AI & Machine Learning: An Enterprise Guide
A collection of information resources designed to help enterprise IT professionals launch and advance their artificial intelligence, machine learning and automation initiatives.
Tools Tackle AI's Bias, Trust Problem
AI and machine learning deployments are hitting the mainstream in enterprises, but executives still hesitate to blindly accept insights from inside the "black box" without seeing the logic behind them.
Where AI Can Turn 'Buzz' into 'Biz' Today
AI can expedite manual processes that exist throughout an enterprise, but the nature of the human insight is necessary to rationally manage these processes and make contextual decisions.
Risk Management Is Evolving: Are You On Board?
IT risk management is a mature topic, but it continues to evolve with technology. As rules-based systems are supplemented with self-learning systems, IT departments, risks managers and business leaders need to update their thinking.
AIOps to Drive Big IT Pivot
AIOps takes the vast amounts of machine data generated by IT infrastructure and ingests, monitors, and analyzes it to ultimately predict issues before they occur.
What Boards and CEOs Should Be Asking CIOs
Boards and CEOs are more tech-savvy than they once were, but they still don't always know the best questions to ask CIOs. With the push for digital transformation they need to be armed with the right questions at the right time.
Help Wanted: Data Engineers Who Fill Enterprise Need
Data engineers build the infrastructure and tools that data scientists and business users need to perform analysis and create machine learning models. Maybe that's why demand is high for this emerging category of IT pro.
What can go wrong with DevOps? Plenty, but you can still learn from your mistakes and the mistakes of other people.