Given the need to justify decisions, vendor selection almost always becomes an endless exercise in analysis-paralysis.
Creation of VMs from a golden image can be automated, but the requirements of each workload are not easy to discover.
One of the most important enduring challenges facing CITOs is making sure that the technology portfolio is aligned at all levels with the needs of the business.
Machine learning has an image problem. It is either not understood or, because of its roots in artificial intelligence, is seen as far off or far out. In truth, machine learning can be a practical business tool within the reach of any enterprise.
Enterprise software of all types has too often been inflicted on individual workers by management, who received little assistance from the products in doing their jobs. Enterprise software created "work about work" for individual workers who used applications to track their work so that executives could see what was going on.
Imagine that wherever you are, in the office or in a remote location, you have all the information that you need to do your job literally at your fingertips, and that you know the same is true for everybody that you’re working with.
Getting value from big data is everyone’s problem, even LOLCats.
Are enterprise IT professionals, like automakers, just hammering pieces into place and ignoring underlying problems?
For most top talent, the work and the people are more crucial than the pay.
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