What Is Big Data?

As a species, we’ve progressed through many different ages. There was the Stone Age, the Bronze Age, the industrial age, and all the other ones in between. However, if there’s one word that will define the 21st century, that’s information.

We’re living at a time where data is more important than money, and the wealthiest companies in the world are proving it. Just take a look at Facebook and Alphabet. For clarification, Alphabet is the company that owns Google and YouTube. Click here to read more.

Their main service is selling information to other companies for money. No one thought that this was going to be what the future looked like, and yet it’s real. You might have come across the term big data, which refers to enormous amounts of data that is collected and growing at an exponential rate.

There are a couple of factors that go in when you have so much information in a single place. That’s how much is there, or the amount, the speed with which it can be accessed and gathered, as well as the variety it represents. There’s even a niche in programming called mining in which developers are trying to access these spreadsheets and then create meaning out of the jumbled numbers.

What makes it work?

When you have so much info about something, you can divide it into either structured or unstructured. We’re going to look at two examples. A bank needs to have your details in order to create a new account. They take your name, surname, date of birth, and your ID number to do a background check on you.

After you get employed, they add your salary. If you take out a loan, they add another column to your name. The info they have about you just keeps increasing. That also happens with every transaction you make. They’re monitoring your spending habits in order to update your credit score.

Eventually, that credit score is going to play a large role when you apply for a loan. All of those factors will determine what kind of interest you will get, as well as the amount you can take. Since all of that information is kept in a structured manner, for example, a spreadsheet or a database, it’s called structured big data.

On the other hand, social media companies work in a completely different manner. Sure, there’s a bit of overlap when it comes to the name, surname, address, and date of birth. But everything else is completely different. Follow this link for more info https://searchcloudcomputing.techtarget.com/tip/An-introduction-to-big-data-in-the-cloud.

That’s due to the nature in which we use social media. Here’s an example. When you first created your Facebook account, you were following pages that you interacted with at that time. In the meantime, you’ve talked to loads of different people, and you’ve posted a bunch of pictures and status updates.

There’s also the comments section where you’ve interacted with other people. Nowadays, the pages you interact with most show up first in your news feed. The same thing is true about the people you talk to most often.

There are so many algorithms in place that are monitoring your activity, and there are carefully placed advertisements that coincide with your interests. This data is called unstructured because it’s subject to constant change.

Marketing companies can buy that information and target you based on your personal preferences. It sounds scary, but that’s what everyone agrees to when they accept the terms and conditions. In some cases, all of this info can be obtained for free if a developer knows how to use APIs, electronic check-ins, product purchases, questionnaires, and applications. This means that ads are going to keep improving.

The benefits and the drawbacks

There are a couple of challenges that arise in the midst of all the possibilities. When it comes to having more info about users, that helps companies and businesses to adapt their strategies to what the public wants.

This ensures better marketing campaigns that ensure people are getting exactly what they paid for. There are loads of analysis tools that aid these calculations. However, one of the biggest challenges in big data is security. It’s critical that businesses understand the ethical weight of having that information leaked to the public.

That’s one of the main things that is still sparking heated debates. Now, more than ever, that needs to be solved because there are new data breaches every year. Additionally, there’s also the possibility of too much information that eventually turns into noise, which makes it less effective.

If you measure everything, then it’s the same as measuring nothing. You need to know how to handle the variables accordingly and set them up by weight. The biggest challenge is deciphering the meaning behind the choices people are making.

This could lead to the phenomenon known as death by multiple choice. The more choices a person has, the harder it gets for them to decide. That’s one of the most renowned laws in marketing. Finally, there’s the issue of organizing unstructured data into something that makes sense.

This includes text documents, videos, and emails. Algorithms are getting better at determining the incentive behind some of them, but there’s still a lot more work that needs to be done. In the future, we can expect more organizations to benefit from this niche.

That includes healthcare, marketing, technology, and financial services. Other sectors need to keep up since the advantage this brings is outstandingly powerful.