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Dangers Of Big Data: How To Minimize The Risks?

The world is moving towards digitization. That's why data is becoming an increasingly crucial element in business decisions. With the advancements in technology, modern-day businesses are adopting big data and cloud storage to get better and faster data processing. We’ve all heard of big data and how companies are utilizing it to function better by getting valuable business insights. However, big data, as promising as it is, comes with a number of risks and dangers.

Businesses utilizing big data should be aware of its risks. After all, the dangers of big data can land businesses in all kinds of trouble including legal issues and threats for cyber-attacks. Fortunately, big data does not necessarily have to be a problem. You just need to know what you’re getting into. In this article, we are going to discuss the potential dangers of big data along with some examples and also see how to minimize these risks. So, without further ado, let’s dive into it!

What is Big Data?

As its name suggests, big data is massive chunks of data that are gathered, stored, and analyzed for revealing valuable business insights. Extracting and managing big data has become an important part of modern business.

Now the question is: why is big data important? Well, put simply, it helps companies make well-informed decisions in a timely manner and perform better risk management. There are 3 main types of big data, with each type having its own technicalities and uses. Following are the types of big data:

  1. Structured Data

  2. Unstructured Data

  3. Semi-structured Data

Are There Any Dangers of Big Data?

For some time now, there’s been a lot of debate on the dangers of big data. A lot of people believe that big data comes with its own set of risks that make it dangerous. When companies collect big data, it raises concerns revolving around data security, privacy, and the consent of parties from which data is being taken.

There are a number of risks when it comes to big data, privacy and security being the most major ones. In the wrong hands, big data can be harmful to a number of stakeholders. Malicious parties can use it for scamming people, identity theft, and more. Managing big data is a major responsibility, which is why it’s considered dangerous by many people.

Dangers and Risks of Big Data

Let’s look at a few negative effects of big data that raise concern. In the past, there have been cases where big data has created trouble for several people. In most cases, big data becomes dangerous when it isn’t handled correctly.

1. Big data’s security issues:

One of the biggest dangers of big data is security. Big data contains sensitive information taken from a very large number of people. In order to work on this data, it needs to be stored someplace. If it’s stored without taking proper security measures, this data can very easily land in the wrong hands. There are a lot of malicious parties out there actively looking for data to exploit. Unfortunately, not every business is equipped with security infrastructure that can keep big data secure from the wrong people.

2. Ethical issues with big data:

Out of all the dangers and risks of big data, ethics are a major concern for a lot of people. This is because when data is being collected for forming big data, a lot of people don’t know that their data is being taken.

Legally, the collection and management of data are still in the grey area. There aren't a lot of definite laws for regulating how organizations can take peoples' data and use it. However, pretty much everyone agrees that taking sensitive information from someone without their consent is wrong.

3. Abuse of big data by malevolent players:

We’ve already established that big data contains sensitive information about individuals that is usually extracted and stored without their knowledge. This becomes even more concerning when there’s a definite chance that malevolent parties may try to steal this data and abuse it.

Data has become a very valuable resource in the modern world. This means that there are a lot of parties out there that are always on the lookout for data that they can steal and exploit. The only way to prevent big data from ending up in the wrong hands is to keep it safe and secure. However, securing data of such proportions requires a lot of resources.

4. Unintentional misuse of big data (including systematic errors):

Some of the lesser discussed (yet important) risks and dangers of big data include unintentional misuse of big data. When being stored and managed, big data goes through a lot of human hands. Improper handling or a general lack of responsibility can result in data being leaked or ending up in the wrong hands as well.

All in all, there are a lot of negative effects of big data that are require a lot of vigilance in order to manage.

Examples of dangerous big data in action

Concern revolving around big data isn’t based on speculation alone. There have already been a number of instances where big data has produced negative effects by ending up in the wrong hands. Let’s go through a few examples of big data gone wrong.

1. Big data and election interference:

The 2016 elections in the US is a classic example of the dangers and risks of big data. After the elections, it became apparent that the results of the elections were manipulated by spreading false information. Further investigation revealed how data was illegally extracted from Facebook and used to manipulate the election results.

Big data can be used to spread misinformation and have a major impact on real-world events. This is quite concerning we are living in the digital age where information travels at a very fast pace. Malicious parties can potentially weaponize data and use it to cause harm on a massive level.

2. Big data and state surveillance:

We’ve often seen and read about dystopian futures where governments use technology to track and monitor citizens. Thanks to big data, this dystopian future is already taking place in China. The country has implemented a social credit system that closely monitors every citizen and gives them a social score. Based on this score, each individual gets (or doesn’t get) access to various services and perks.

China’s social credit system shows us just how dangerous and intrusive big data can become if used for the wrong reasons. This is one of the freshest and real examples of big data gone wrong.

3. Big data and racial profiling

Big data can produce biases that can be harmful to certain groups within a community. A recent example of the negative effects of biasness in big data is how Amazon's facial recognition software ended up labeling certain members of Congress as criminals. A majority of the falsely labeled people were people of color.

Further investigation revealed this was caused by the data set being biased. If a data set contains a bias, there is a possibility that its biasness can be carried forward and result in problems such as racial profiling.

How to Minimize the Dangers and Risks of Big Data?

Big data can be problematic when handled incorrectly. This doesn’t mean that we should simply boycott it. There are a number of proven advantages in analyzing big data that we simply cannot ignore.

Big data has the potential to change the future, this is why it is so important. Its risks and dangers can be minimized if certain steps and precautions are taken. For instance, we can minimize the negative effects of big data by formulating guidelines, laws, and ethical boundaries that refine the process of managing big data.

1. Improve and Prioritize Data Security

When storing big data, organizations should take extra measures to ensure proper security. Therefore, businesses should always use data servers that have multiple layers of security. Also, organizations should make sure that there are fail-safes in place. Most importantly, it’s critical to manage data access so that only authorized people can access it.

2. Only Collect Relevant Information

By collecting data in an ethical manner and stripping it of additional information (such as names), it can be made a lot safer. Apart from cleaning data as it’s collected, organizations should also remove data that is no longer needed. Practices such as these can decrease the risks and dangers of big data by making it less volatile.

3. Implement Data Compliance Laws

The legal side of collecting and managing data is quite vague. While there is a data protection act, it isn’t enforced and followed in many parts of the world. Improper compliance results in the data protection act losing its weight. Therefore, data analysts around the world should make an effort to comply with this act.

4. A Hippocratic oath of big data

In order to make a difference on a large scale, we have to start at an individual level. One way of doing this is by instilling a Hippocratic oath (like the one that doctors across the globe follow) that asks data analysts to be responsible when it comes to handling data. The idea of adopting an oath isn’t too popular. However, if adopted, it can help decrease the negative effects of big data.

Final Thoughts

Big data is a double-edged blade. While it has certain dangers and risks, there are also a number of positive effects of big data. If handled responsibly, big data can be used to help businesses grow. This in turn can increase economic growth. Apart from being beneficial for businesses, big data also helps make breakthroughs in vital research. You can check our comprehensive article on “Future of Data & Analytics" to get a better idea of how Big Data can revolutionize modern-day businesses.

Based on its positive impacts, it’s hard to say that we should boycott big data. Instead, we should make an effort to regulate its management and analysis. With enough effort, big data can be tamed and turned into a very valuable commodity. If you want to utilize Big Data in your business without exposing yourself to its dangers and risk, you need to partner up with a highly experienced and professional data management company like IIInigence.

Here at IIInigence, we stand proud as one of the best data management companies in the USA offering a variety of data management services powered with AI, including data analytics, data mining, data warehousing, etc. We are fully aware of the dangers associated with big data and always take full precautions to avoid any risks and give you the maximum value. Reach us by filling out the contact form on our website or simply call us on our given phone number to discuss your ideas in detail.

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