Big Data and Privacy Issues Arising Out of It

Big data has been a phenomenon for the last decade or so. Big data analytics have a number of uses in everyday life, but its most significant use has been in improving businesses. For instance, big data analytics can help retail businesses predict the most popular items each season, and also predict which items will be popular in which places. This helps businesses improve sales and customer satisfaction. The power of big data is being utilized by several industries. But with massive power comes the concern of privacy issues. While big data analytics prove helpful in a lot of ways, they also make it easy to invade privacy in the following ways.

Big Data and Privacy Issues Arising Out of It

Big Data and Privacy Issues Arising Out of It

Privacy Breaches

Some uses of big data analytics result in the breach of privacy. For example, retail businesses often use big data analytics to predict customers’ details. These details are often personal in nature, and disclosing them can lead to lost jobs or uncomfortable situations. Organizations, retailers, or any other type of business should not take actions that breach the privacy of people.

Impossible Anonymity

With big data analytics, it could become impossible to have anonymized data files. In the age of smart gadgets, it is hard to do anything keeping your identify secret. Even when data files are anonymized, they could be combined with other files to identify individuals. This means no one is completely anonymous anymore.

Discrimination

While discrimination has always existed in every sector, predictive analytics has only made it more commonplace and in a way that’s not truly objective. For instance, a financial organization may not be able to determine a person’s race from a loan application, but could do so with the help of several other data collected through big data analytics and the Internet of Things (IoT). Then an applicant’s loan request could be turned down. This kind of ‘automated discrimination’ can backfire in most cases.

Data Masking Failure

Data masking is used by a lot of organizations, but if it isn’t used properly, then big data analysis could easily reveal the identity of the individuals. Big data is still very new, and most organizations don’t care about the risks that could lead to breach of privacy. There should be a proper policy in place that lays down rules for data masking, to ensure the maximum privacy of individuals.

No Complete Accuracy

Even though big data analysis is powerful, it isn’t completely accurate. There are flawed algorithms, incorrect data models, and inaccurate data about individuals. This could facilitate bad decisions, if the accuracy of the data is not validated. Inaccurate data can harm individuals, and cause loss of job, false misdiagnosis, and denial of essential services. If big data analysis is trusted blindly without any verification of the data, it could lead to a plenitude of problems and put many people at risk.

Irrelevance of Parents and Copyright

Big data could make it harder to obtain patents because it would take a long time to verify the uniqueness of the patent, thanks to the huge database of information to look through. It would also make copyrights irrelevant, because big data makes it easy to manipulate and hide data. As a consequence, royalties associated with patented or copyrighted information could become a thing of the past. That would be not good considering there is much hard work in inventing something new. If you want to see an excellent movie on this, see the kitchen product that that young woman invented in the movie Joy. Her own family was scandalous as well!

How to Tackle Big Data Privacy Issues

While big data analytics is very promising for businesses and inspires significant developments across various organizations, the concern for privacy is a major consequence. Before using big data analytics, organizations must always keep a few things in mind. Some of these are:

  • Before putting big data analytics to use, organizations must consider at least ten privacy risks associated with the strategy.
  • There should be clear rules, policies, and guidelines for big data analytics uses that safeguard the privacy of individuals.
  • There must be security and privacy controls incorporated into the system before putting them into use.

Final Thoughts

Technology is a necessary tool for every modern business, and big data is the most powerful technological innovation in recent times. Like every technology, there is a good and a dark side of big data analytics—while helping organizations in their business process, big data also regularly breaches privacy and data security. Having proper guidelines and rules in places should help to make better use of big data analytics without putting privacy at stake.

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