A Quote by John Poindexter

TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue. — © John Poindexter
TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
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.
What is clear is that users own their data and should have control of how their data is used.
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.
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 like to say I've been working on big data for so long, it used to be small data when I started working on it.
When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern has been privacy - the disclosure of sensitive data about individuals, either directly to the public or indirectly from anonymised data sets through computational processes of re-identification.
As individuals, we have very little say about how our data is being used. I'm not worried about the privacy implications of it so much. But it seems to me that, as an individual, if I'm the one generating the data, I should have some kind of say in how it's going to be used.
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.
We all say data is the next white oil. [Owning the oil field is not as important as owning the refinery because what will make the big money is in refining the oil. Same goes with data, and making sure you extract the real value out of the data.]
I promoted Hyderabad to the world by saying that there was privacy in India and their data will be sage. Data is wealth.
Users get unlimited 'WhatsApp'. We get happy users who don't have to worry about data. Carriers get people willing to sign up for data plans.
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.
While many big-data providers do their best to de-identify individuals from human-subject data sets, the risk of re-identification is very real.
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.
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