This might be controversial, but 5-9’s of availability just doesn’t seem to cut it anymore in today’s cloudy, more hyperscale, consolidated data center storage infrastructure. In fact, we deserve much …
Whether driven by direct competition or internal business pressure, CIOs, CDOs and even CEOs today are looking to squeeze more value, more insight and more intelligence out of their data. They no …
We are always driven to try to do smarter things faster. It’s human nature. In our data centers, we layer machine learning algorithms over big and fast data streams to create that …
When we want to start computing at biological scales and speeds – evolving today’s practical machine learning forward towards long-deferred visions of a more “artificial intelligence” – we’ll need to …
Machine learning is the force behind many big data initiatives. But things can go wrong when implementing it, with significant effects on IT operations.
Unfortunately, predictive modeling can be fraught with peril …
At this month’s Hadoop Summit 2015 I noted two big trends. One was the continuing focus on Spark as an expansion of the big data analytical ecosystem, with main sponsor …
