What makes this contest in particular interesting is that the organizers are stretching beyond the expected applications in agriculture, construction and renewable energy by also deliberately inviting new services and products in "forward-thinking segments such as big data, cloud computing, crowdsourcing, data visualization, mobile applications, and more."
Amazon Machine Learning takes on IBM's Watson, Google's Prediction API and Microsoft's Azure Learning
As expected, machine learning is making its way to the masses. But first it's coming to developers free of any need to master statistics first. And, boy, is the field getting crowded with giants.
Once big data becomes fully consumerized, it will be possible for anyone to identify anyone based on anything from religious affiliation, sexual preference, political association, even something as trivial as rival sport team fanhood, which can then be used by individuals to discriminate against entire groups of people. Everyone will be at risk from someone. In a world totally deprived of privacy, there is little to no protection from those that vehemently disagree on basically anything.
If, like me, you'll be attending the EDW conference this week in Washington, D.C. and you have news to share, please email me that information with your contact info so that I can reach you at the event or follow-up with you afterwards. As to the rest of you dear readers, stay tuned for news rising out of this event.
App analytics help developers promote their apps but a new self-service authoring tool makes it possible for non-developers to make mobile apps to compete with developers' apps.
Big data is hard work and it's changing everything, even the way you think. So how can you assess how your new way of thinking measures against those in the C-suite? One way might be to use a new benchmarking tool from the Economist Intelligence Unit and Platfora to "find out where you fit in to the spectrum of C-Suite understanding of big data."
According to recent research, nearly every medical information website--from About.com and CDC.gov to Health.com and university websites--is collecting and monetizing information based on searches about symptoms or diseases.
To help vendors, app developers, and other interested parties sell big data products, services, and ideas to the government, I asked a panel of federal government agency leaders to share what government agencies are interested in buying and to reveal how best to sell to them.
Much has been said about the challenges in using big data, from data scientists having to spend too much time on data janitor duties, to adoption resistance stemming from corporate culture. Still, the biggest hurdle by far is in the Business-IT divide. Until business and IT reach a point where they truly understand each other and work as a team, big data and other initiatives will continue to falter and fail.
Yes, data scientists are the sexiest beings on the planet but that doesn't mean they get the superstar treatment they deserve--frustrations are high. Everyone wants big data but they don't understand it, yet they try to manage the data scientists. It would be funny if it weren't so darn destructive.