A Quote by N. Chandrababu Naidu
I promoted Hyderabad to the world by saying that there was privacy in India and their data will be sage. Data is wealth.
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TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
When a handful of tech giants are gatekeepers to the world's data, it's no surprise that the debate about balancing progress against privacy is framed as 'pro-data and, therefore, innovation' versus 'stuck in the Dark Ages'.
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.
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'm not targeting government. I'm not saying hey, I'm closing it because I don't want to give you any data. I'm saying that to protect out customers, we have to encrypt. And a side affect of that is, I don't have the data.
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.
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.
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 dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
The NSA is not listening to anyone's phone calls. They're not reading any Americans' e-mails. They're collecting simply the data that your phone company already has, and which you don't have a reasonable expectation of privacy, so they can search that data quickly in the event of a terrorist plot.
I will talk about two sets of things. One is how productivity and collaboration are reinventing the nature of work, and how this will be very important for the global economy. And two, data. In other words, the profound impact of digital technology that stems from data and the data feedback loop.
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.
I'm worried about privacy - the companies out there gathering data on us, the stuff we do on Twitter, the publicly scrapeable stuff on Facebook. It's amazing how much data there is out there on us. I'm worried that it can be abused and will be abused.
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.
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