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Sharing Big Data Safely by Ellen Friedman, Ted Dunning

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Chapter 2. The Challenge: Sharing Data Safely

Sharing data safely isn’t a simple thing to do.

In order for well-protected data to be of use, you have to be able to manage safe access within your organization or even make it possible for others outside your group to work with secure data. People focus a lot of attention on how to protect their system from intrusion by an attacker, and that is of course a very important thing to get right. But it’s a different matter to consider how to maintain security when you intentionally share data. How can you do that safely? That is the question we examine in this book.

People recognize the value and potential in collecting and persisting large amounts of data in many different situations. This big data is not just archived—it needs to be readily available to be analyzed for many purposes, from business reporting, targeted marketing campaigns, and discovering financial trends to situations that can even save lives. For instance, machine learning techniques can take advantage of the powerful combination of long-term, detailed maintenance histories for parts and equipment in big industrial settings, along with huge amounts of time series sensor data, in order to discover potential problems before they cause catastrophic damage and possibly even cost lives. This ability to do predictive maintenance is just one of many ways that big data keeps us safe. Detection of threatening activities, including terrorism or fraud attacks, relies on having ...

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