A Quote by Isa Briones
They made it very clear that I shouldn't try to be Data because there is only one Data, you can't ever recreate the magic that Brent Spiner made.
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Connectivity offers a great opportunity for General Motors. When you look at the investment we have made in OnStar and putting 4GLT in and the access you have to not only put data in, and we haven't really tapped into the data you can use from the vehicle.
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.
I wanted to separate data from programs, because data and instructions are very different.
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.
What is clear is that users own their data and should have control of how their data is used.
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.
Disruptive technology is a theory. It says this will happen and this is why; it's a statement of cause and effect. In our teaching we have so exalted the virtues of data-driven decision making that in many ways we condemn managers only to be able to take action after the data is clear and the game is over. In many ways a good theory is more accurate than data. It allows you to see into the future more clearly.
We are ... led to a somewhat vague distinction between what we may call "hard" data and "soft" data. This distinction is a matter of degree, and must not be pressed; but if not taken too seriously it may help to make the situation clear. I mean by "hard" data those which resist the solvent influence of critical reflection, and by "soft" data those which, under the operation of this process, become to our minds more or less doubtful.
No great marketing decisions have ever been made on qualitative data
This years keynote session is a clear reminder that wireless data technology is expanding its reach beyond that of an alternative to wireline telephony. We have gathered an exclusive group of business leaders to share how wireless is being integrated into their companys business strategies and what it means for their bottom lines. The presence of these telecom, media and entertainment giants on our center stage is a great indicator of the impact wireless data has made on countless industries.
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.
Nobody should try to use data unless he has collected data.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
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.
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.
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