Business Knowledge

How Global Companies are Using Big Data to Predict the Future

“Scientia potentia est” or “Knowledge is power” is an old adage we’ve all heard, and the modern equivalent of this old saying would be “Data is Power.” Looking at global economies, historical trends, and technological innovations, we’ll see one thing that completely stands out in the past half-century, and it is data. Not only the rate at which the data is generated but also our ability to collect and analyze data has been exponentially exploding for the past 20 years, but we see big economies like EU and the US move away from traditional manufacturing and production and focus on creating a ‘knowledge-based economy.’ An economy that puts information and knowledge at the heart of its business activities and investment plans. Not only digital businesses are utilizing the data to take more data-oriented decisions, but data science is also playing a vital role in advancing medicine.

This article focuses on key actors that are at the forefront of this movement, the international corporations. Why they store so much data, how they use this data to predict the future, and how this ensures their long-term growth and survival in the global market.

Data Collection, It’s Free

Perhaps the biggest reason for storing and using user data has become the norm is the laws regulating the internet. Ever since the dot-com bubble, when the number of tech companies started exponentially increased, the governments around the world have failed to keep up in terms of regulatory and bureaucratic power.

In reality, while there have always existed some rules governing data and its uses, due to the fluidity of the medium, companies have always found a way around them. Not to mention, as data collection is hardly a physical activity and doesn’t leave any traces, it is much harder to detect and prevent abuses. This has virtually meant that companies can collect any sort of information they want about their users: location, income, behavior, race, etc. This glaring problem came to a front during 2016 when high profile abuses and loopholes were talked on the international stage. Although some measures have been taken, they are still not enough to regulate data collection to a meaningful degree.

Big Data Architecture

Moore’s law is in the heart of the new industry, too. It was just 3 decades ago that 1GB of storage was a substantial cost for a business. Our ability to store, access, sort, and modify data has increased at an astounding rate.

Although, something no one expected was how big of a deal software will play along with hardware. Right now, petabytes of storage are available to every business at relatively low costs, today your storage system can expand and shrink depending on demand, and, you now can integrate data centers around the world seamlessly. All of these technologies were stepping stones to bring about the knowledge economy, the data revolution, and unprecedented demand for data analysts and data scientists.

The Result

You might be surprised to learn, but we’ve had fairly advanced machine learning algorithms since the 80s. The biggest problem back then was collecting and large amounts of data to run the algorithms on.

Now, that storing large amounts of data was cheap and the infrastructure was widely available, only one thing remained, running algorithms on the data to make sense of it and predict the future.

In the beginning, the predictions were modest and fairly unremarkable. Businesses could predict demand for certain products slightly ahead of time, they could see cyclical business patterns, and they could analyze some trends to make come up with better long-term planning. It is important to note that even these modest predictions could bring millions in revenue for big corporations. This incentivized them to invest in better hardware, research, and talent, to the point that most big companies now have their own research department that only analyzes user data and wider market trends.

This market forces, incentives, globalization, and technological advances effect on companies having to adopt big data strategies can all be summed up in a single news story. In 2012, Target was able to predict a girl was pregnant before her family even knew about it. It caused quite a stir as they send the girls ads and coupons targeting pregnant women and her family become concerned and weirded out by it. It doesn’t stop there – companies now have access to your purchasing pattern, data going back to a couple of years, and even your social groups. This gives them unprecedented insight into your daily behavior and general life and makes it possible for them to predict and learn a lot of things about you.

What will happen in the future? Governmental bodies are already trying to limit corporations’ access to personal data. On the other hand, the industry isn’t slowing down and new avenues for data collection open every day. No one is able to predict the future, but, it is most likely this industry is going to keep growing at least for the foreseeable future.

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