Data collection is not a recent development. We have been collecting data for centuries. The term data collection is, of course, a modern-day explanation of the process. The term Big Data was coined recently in 2005. It labels the enormous quantities of information called data sets. They defy traditional methods of analysis and can offer huge benefits if used effectively. Today, everyone, including government offices and private businesses, is tapping into big data to unlock its potential. However, while the potential benefits of Big Data are enormous, it also comes with some significant risks, leaving people still asking: is big data dangerous?
The Risks of Big Data
Reams of documents have been written about the benefits of Big Data. However, it is not exactly a bounty of progress.
Big Data potentially poses severe risks if not gathered correctly, stored securely, or used incorrectly. The key to avoiding and overcoming these is to understand them.
The risks associated with Big Data divide into three main categories:
- Security issues
- Ethical issues
- Deliberate abuse
The more data an organization collects, the more difficult it is to store securely. This also is why some might think big data is dangerous. Certainly, data breaches are becoming common, even in organizations with advanced security and storage systems. The issue of privacy connects to security. Moreover, social media conglomerates, government agencies, insurance giants, and healthcare services have various levels of access to our data.
Yet, data protection laws bind them. Although, the unprecedented numbers of data breaches in recent times show more needs to be done on this front. No company can sit back and claim that their data is beyond the reach of hackers. There are too many instances of data hacking of reputed organizations that disprove this claim.
Many organizations have easy access to our private information. They know our address, what we do, how much we spend, where we go for vacations, etc. Even our bank details and other sensitive information can be accessed with a few clicks. That’s why data security is a significant area of risk with Big Data.
We may assume that organizations manage to keep our information protected from hackers and cyber-attacks. Yet, there is this likelihood that they might misuse the information for their personal gain. Data protection laws are in place. But still, some grey areas exist around how companies use data when obtaining it legally. Take the example of credit card companies and insurance providers.
Take insurance providers and credit card companies. It’s certainly no shock that many of them calculate premiums and limits based on customer behaviors. Big data provide them with the input to make highly refined predictions.
There are many other ethical issues, too, involving consent, privacy, and ownership. These have resulted in the formation of new laws.
Deliberate Data Abuse
Is big data dangerous? A major risk with big data is third parties potentially getting their hands on sensitive information. It is estimated that 2.5 quintillion data was generated daily in 2020. That’s an immense amount of data and undoubtedly far more than any organization can manage or analyze efficiently. Hackers and cyber attackers are forever trying to target this data. They can access it illegally and sell it on the Dark Net to make pots of money.
We read news about bank frauds, insurance scams, phishing, cyber-attacks, etc. Indeed, these are typical examples of how organized crime syndicates can deliberately misuse and abuse big data. Scams have become sophisticated, and some truly audacious ones have recently been pulled off.
Big data also plays a role in the misinformation and spread of fake news. This is also a form of abuse. Nefarious organizations can use big data to create fake news. Certainly, such types of content influences our ideas and beliefs on purpose. Nowadays, even winning elections and forming governments mean interference from such influences.
How to Mitigate the Dangers of Big Data
It is crystal clear that big data poses clear risks and dangers. However, that doesn’t mean we should stop using data – that’s impossible and irreversible.
It is equally clear that the potential for positive changes is also huge with Big Data.
Big data analytics is a relatively new discipline. So, the best way to deal with data threats is to learn from mistakes and boost safety and security measures. Indeed, we can reap big data’s benefits by implementing the best security features and improving ethical guidelines. This also helps us take those vital steps toward mitigating significant data risks.
The potential of big data is vast. It can be utilized to garner even more powerful insights and transform our private and professional worlds. Certainly, security issues will always be a part of big data. Bad players will continue to abuse data and try to use them for their personal gains.
The battle between big data’s positives and whether big data is dangerous will be ongoing. So, the best way of minimizing risks is to identify and acknowledge their potential risks. Certainly, every big data user must do their part to encourage a culture of integrity within data science. The key is to place adequate safeguards in place and review and update them regularly.