A Quote by Huda Kattan
We know now data is so powerful, and you can learn so much about yourself and creating product with data.
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We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.
People believe the best way to learn from the data is to have a hypothesis and then go check it, but the data is so complex that someone who is working with a data set will not know the most significant things to ask. That's a huge problem.
Facebook collects a lot of data from people and admits it. And it also collects data which isn't admitted. And Google does too. As for Microsoft, I don't know. But I do know that Windows has features that send data about the user.
Design has a powerful impact on the viewer. It has authority, and data also has the same air of authenticity and detail. It can be hard to argue with a graph, and it's hard to argue with data. So to combine data with a strong visual impact creates a powerful message.
The first wave of the Internet was really about data transport. And we didn't worry much about how much power we were consuming, how much cooling requirements were needed in the data centers, how big the data center is in terms of real estate. Those were almost afterthoughts.
My study is NOT as a climatologist, but from a completely different perspective in
which I am an expert … For decades, as a professional experimental test engineer, I have analyzed experimental data and watched others massage and present data. I became a cynic; My conclusion - 'if someone is aggressively selling a technical product who's merits are dependent on complex experimental data, he is likely lying'. That is true whether the product is an airplane or a Carbon Credit.
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.
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.
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.
With too little data, you won't be able to make any conclusions that you trust. With loads of data you will find relationships that aren't real... Big data isn't about bits, it's about talent.
Scientists learn about the world in three ways: They analyze statistical patterns in the data, they do experiments, and they learn from the data and ideas of other scientists. The recent studies show that children also learn in these ways.
... negative feelings are not true feelings at all; rather, they are your thoughts about something, based always on the previous experience of yourself and others. You will not find Truth in your past data, only past data that is based on other past data that is based on other past data, and so forth. Forget your "past experience" and look directly at the experience you are having. Right Here, Right Now. There is your Truth.
You have to imagine a world in which there's this abundance of data, with all of these connected devices generating tons and tons of data. And you're able to reason over the data with new computer science and make your product and service better. What does your business look like then? That's the question every CEO should be asking.
We know everything about what you know and how you learn best because we get so much data. And education is the highest-stakes media product in your life. It's infinitely more important than your Facebook friends' status updates or your Google search results because it's your future.
MapReduce has become the assembly language for big data processing, and SnapReduce employs sophisticated techniques to compile SnapLogic data integration pipelines into this new big data target language. Applying everything we know about the two worlds of integration and Hadoop, we built our technology to directly fit MapReduce, making the process of connectivity and large scale data integration seamless and simple.
Big data is great when you want to verify and quantify small data - as big data is all about seeking a correlation - small data about seeking the causation.
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