5 Survival Tactics for Enterprise CIOs in 2018
Longtime tech industry pundit Tim O'Reilly sat down with InformationWeek to talk about the future of business, society, and the enterprise. Here's what he says enterprises must do to compete in a changing business environment.
IT Versus the Organization
There are significant gaps in how IT professionals and business leaders view issues such as aligning tech with business goals. Experts share some thoughts on how to close the gaps.
How CIO/CFO Relationships Are Evolving
In an era when organizations have to move forward quickly with innovative -- often expensive -- tech initiatives, CIOs and CFOs may have to form a partnership.
Beware Analytics' Mid-Life Crisis
Analytics is spreading out to more departments that want to optimize their operations, but that may give users a false sense of freedom from IT. Here are some dynamics currently affecting IT.
How to Spin off an IT Startup
Executives who have done it share their experiences and advice on knowing when and how to spin off an IT-based startup.
Clear the Barriers to DevTestOps
A key to a successful DevOps initiative is ensuring that team members stay involved at all stages of the development, test, and deployment cycle.
IT Job Satisfaction on the Upswing
IT was once viewed as a back-office function, filled with disgruntled, reserved workers, but the view of the IT role and worker is changing, and it's showing in IT job satisfaction levels.
DevOps Benefits Shine Through at Summit
Real-world DevOps implementers highlight how varied organizations discovered benefits from DevOps, even if they had to clear some hurdles on the path to success.
5 Tech Trends That Will Redefine Your Business
Digital transformation requires fundamental changes to the business. Are you ready yet? If you're not thinking about how the following 5 trends affect your business you need to start doing so now.
Why Automation Won't Displace Human Intelligence in Analytics
There's great value for companies to use automation technologies in analytics, taking advantage of the vast data sets now available. Making machine learning models more precise isn't just about technology; but a reimagination of business structure and the roles of tech and people.