When the internet was conceived, many people believed it was the pinnacle of digital communications. It enabled users to share information despite being continents away seamlessly. And as the online repository of unstructured data grew to a massive scale, technology pioneers began connecting the dots and took digital information-sharing to a whole new level.
Today, big data has become one of the most promising concepts in the tech space. You can find it everywhere — from music streaming services to hospitals that store medical records digitally. Big data analytics also enable businesses to refine their lead and customer engagement strategies as well as execute data-driven marketing campaigns.
But what if you’re an everyday user who’s never even heard of big data before? What if you’re simply an employee who’s in no position to worry about big data analytics?
Chances are, you might consider giving up some of your information to certain brands in exchange for personalized services and experiences. This, however, could open up gaping holes in your online security and privacy. After all, the World Wide Web is no stranger to embarrassing data breaches that endanger the information of users such as yourself.
Without further ado, here is a closer look at three of the biggest risks in a world that runs through big data:
Services are requiring more sensitive information
Have you heard of password managers? What about digital wallets that do the honor of storing your credit card information? Given the sensitivity of information that these services handle, you might think that they have an impenetrable security technology under the hood. That is, until you realize that companies like LastPass and credit bureaus like Equifax can be hacked if the perpetrators are skilled enough.
If you are willing to put sensitive information on the line for the sake of convenience, at least consider alternatives to avoid putting all your eggs in one basket. Sure, LastPass has long been recovered, look at possible alternatives like Dashlane or Zoho Vault.
Also Read: How-big-data-is-helping-your-commute-to-be-safer-and-faster
Data discrimination and inaccuracy
Big data is widely utilized in a variety of automated and predictive processes. The initial goal is to save time, reduce costs, and diminish the likelihood of human error. Unfortunately, systems sometimes misinterpret data and cause unintentional discrimination in automated decisions. These could undermine not only the privacy of individuals but their right to fair treatment and equal opportunities.
“Data mining can inherit the prejudices of prior decision-makers or reflect the widespread biases that persist in society at large,” said Solon Barocas of the Center for Information Technology Policy at Princeton. “Advocates of algorithmic techniques like data mining argue that they eliminate human biases from the decision-making process. But an algorithm is only as good as the data it works with.”
For example, big data is now being integrated into systems that automate sourcing and employability assessment. With these in place, errors in the process of compiling data could lead to companies that unjustly discriminate against population segments. Another instance is when Facebook was once discovered to offer real estate ads that exclude certain ethnic groups or races—an issue that’s now fixed through patches in the network’s ad targeting.
Big data is rapidly getting bigger
As an end user of technology, you probably generate heaps of data points on a daily basis. It happens when you perform a Google search, view an online product page, or use any cloud-based app that requires an account. You probably even upload information voluntarily by “checking in” at locations through Facebook.
Put simply; big data is assuming greater roles in our everyday life. And the more you use it, unknowingly or not, the more you put at stake. Always remember that cybercriminals are getting craftier with the ways they steal information; even big name brands are vulnerable to their exploits. It costs nothing to be a little more careful when disclosing information—even to brands you trust.
A rule of thumb is only to supply details that are absolutely necessary to complete a transaction. And when using apps or webs that collect information in the background, one method to consider is to connect through virtual private networks or VPNs. These are also useful to stay protected when connecting to public Wi-Fi networks. To learn more about VPNs, you can start with this review of HideMyAss, which is one of the most popular VPN providers in the market.
Conclusion
In a data-driven world, you can never be too safe when it comes to privacy and security. It can sometimes be risky, but it’s clear that the advantages of big data far outweigh the potential drawbacks. It’s here to stay, and it’s in your best interest to conform with vigilance.
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