A Quote by Jeremy Stoppelman
Yelp is in a very nice spot: local data, and especially review data, is one of the killer apps on mobile phones.
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On mobile, what are the core apps? It's basically messaging, mapping and review data.
There's a large percentage of mobile phones that now have a camera that's with you a lot of the time, and there's a lot of interest around those cameras as a data collection mechanism.
Data is gathered all the time. Just take your mobile phone. Geo-location data collected by your (mobile phone service) provider is not just about your movements. It's about who you are with and what you will do next.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
Personal computing today is a rich ecosystem encompassing massive PC-based data centers, notebook and Tablet PCs, handheld devices, and smart cell phones. It has expanded from the desktop and the data center to wherever people need it - at their desks, in a meeting, on the road or even in the air.
The SP-i600 by Samsung with Windows Mobile software provides a great mobile phone experience that allows mobile professionals to be more productive and effectively manage their busy lives with seamless access to their data and the Internet when they are away from the office.
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
Any time scientists disagree, it's because we have insufficient data. Then we can agree on what kind of data to get; we get the data; and the data solves the problem. Either I'm right, or you're right, or we're both wrong. And we move on. That kind of conflict resolution does not exist in politics or religion.
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.
In my view, our approach to global warming exemplifies everything that is wrong with our approach to the environment. We are basing our decisions on speculation, not evidence. Proponents are pressing their views with more PR than scientific data. Indeed, we have allowed the whole issue to be politicized-red vs blue, Republican vs Democrat. This is in my view absurd. Data aren't political. Data are data. Politics leads you in the direction of a belief. Data, if you follow them, lead you to truth.
I wanted to separate data from programs, because data and instructions are very different.
Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.
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