But let’s dig past those reasons to understand a somewhat hidden motivation to fully adopt privacy-centered measures in data science: the boost to innovation itself.
Growing Privacy Concerns
If you’ve been following the news over country email list the last few years, you’ve surely come across stories about digital breaches that violated the privacy of millions of users’ data. In a certain way, it feels like this kind of scandal happens way too frequently.
Thus, it’s not a surprise to learn that a survey conducted by Pew Research has found that 79% of people are very or somewhat concerned about how companies are using the data they collect about them.
Innovation Is Inherently Data-Based
In a great read from a couple of years ago, BairesDev’s own CEO, Nacho De Marco, took a deep look into what innovation means today and what businesses can do to achieve it. The entire article has many interesting takes, but I want to with its robust solver integrations highlight one paragraph in particular:
“Things like artificial intelligence, data science, the Internet of Things, and blockchain are changing everything around us, so the process of using them to rise up to the challenge and adapt to the new context is essential. You can call that innovation, lateral thinking, revolution, or whatever name you like. The important thing is to embrace the evolutionary process.”
Privacy First Is Essential for Innovation
So, on one hand, we have virtually all vietnam data innovations relying on readily available data to take place. And on the other hand, there’s a growing reluctance from people to give away their information because of security and privacy concerns. What’s the only way forward, then? For organizations to recapture people’s trust in their ability to keep data secure from attacks and private from prying eyes. In other words, to embrace a privacy-first approach to data.