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Big data: What it is and why it matters

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If you’re part of a large-scale company, you’ve probably hear the term “big data” thrown around once or twice. Even if you’re not, you’re probably aware of the term and the recent attention it’s received. But knowing what big data actually means is much less common. Are we talking about megabytes versus gigabytes and the relative size of storage? In short, no, although we can explain. This article will help anyone who wants to know what big data is and why it matters. It’s relevant information even for people who aren’t involved in business or analytics, since each one of us helps compose these data sets whether or not we’re aware of it. Let’s break it down.

Big data: What it is and why it matters

What is big data?

If you type that question into a search engine, you’ll need to filter through thousands and thousands of results—each with a varying definition. Here marks the beginning of our lesson: what you see listed on the first page of your results is a prime example of how big data works. Google has taken a massive amount of information and, using big data analytic techniques such as machine learning and predictive analytics, has presented you with the results it deems most relative (in just .62 seconds, if you’re running on my Wi-Fi speed!). Big data refers to sets of data that are so voluminous and complex that traditional data processing software is inadequate to handle them. Companies can create these sets by pulling data from both traditional and digital sources, either inside the company, outside the company, or both. Data streams from everywhere: phones, credit cards, televisions, computers; from sensor-equipped chairs to carefully-tracked trolley times. Information science collects these massive data sets to then make meaning out of all the numbers. Why was the train late? Do my employees work more efficiently in cooler air conditioning? How much does that air conditioning cost with relation to their increased output? Once you formulate a question in mind, big data can probably solve it. For example, big data analysis can create neural network translations and self-learning machines with artificial neurons. Or, it can be used for data-driven marketing to more effectively reach consumers. Its potential is seemingly endless.

Why does big data matter?

The big data revolution and the movement for quantification is controversial, as is most technology that questions the invasion of privacy. Going back to the earlier search result example, I don’t recall ever expressly telling Google where I live, so how did it know to provide me with results relative to my location? Did I hit “agree” to some fine print that I didn’t read? Or maybe it’s keeping track of my previous searches, and learning that I frequently look for mechanics, concerts, and good ice cream in the same area? Whatever the case may be, it becomes kind of creepy to think about; nonetheless, we’re pleased with the convenient results we see in .62 seconds and don’t stop to think about its implications. What about the other results listed on pages 2, 3, or 4 that might have had better, more accurate answers but the computer decided weren’t as relevant? Although it’s true that Google has done an incredible job developing their algorithms to offer the best results, some still remain skeptical. And remember, this is just one example of how big data works.

Big data: What it is and why it matters

What you can do

How you choose to respond to big data is your choice. As a consumer, you can disable all of your location permissions, cut up your credit cards, toss out your cellphone, sell your home and go off the grid completely – but that sounds a little extreme, don’t you think? A better solution to handle the big data you’re enmeshed in is to be aware of the permissions you grant, those “agree” boxes you mindlessly click, and the way big data is being used on you. As an employer, using big data sets to solve problems or drive profits isn’t some sort of sin, and many business gurus would encourage you to use it to your advantage. As long as you remain ethical – and include legal disclaimers regarding the information you pull – it shouldn’t pose a problem to you, your employees, or consumers. Some say you can’t manage what you don’t measure; if you agree, start researching big data analytic software and see if it’s the solution for you.

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1 Comment

  1. sanne-jerxsen@prodoc.de'

    Sanne Jerxsen

    November 16, 2019 at 7:37 pm

    You are mentioning neural translation as an application of big data. This is an example that also shows the shortcomes of big data. If you want to use Google translate, DeepL or any other free translation service, the results the deliver will depend on what kind of input they got. Therefore it is crucial to be critical and check the output for consistency and terminology used. We explain this problem in more detail in our page on machine translation.

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