By Linda Castaño, Data Scientist at DataKnow
It’s interesting to think about how the history of our society somehow “repeats” itself. Let me give you some context, I’m referring to mining, for some reason, we have a certain fixation on mining things. There is information indicating, for example, that coal as a mineral has been used in China for about 2000 (yes, two thousand) years. For decades, men risked their lungs to extract the black mineral.
We can also mention the Gold Rush that took place in the United States, specifically in California, between 1848 and 1855. This so-called Gold Rush mobilized many immigrants who sought to get rich with this precious mineral. Clearly, this event had a significant impact on the economy of the time.
Moving to more current times, we have cryptocurrencies. The story of the mysterious Satoshi Nakamoto and how he created cryptocurrencies already sounds like an urban legend but is quite real. Nakamoto did something that 20 years ago would have seemed absurd and impossible: create a decentralized digital currency that no state controls. I think we all know how these intangible currencies are doing. Nowadays, many people mine and invest in cryptocurrencies, and there are more than I can count.
This latter (Bitcoin mining) has some similarities to Data Mining, since at the end of the day, both deal with data. It’s worth clarifying that, beyond the fact that in a way, both involve mining data and both have marked a before and after in our history, they are entirely different fields.
What is Data Mining and Big Data?
Data mining is a series of technologies and techniques used to extract information from massive amounts of data generated by customers, users, and devices connected to the internet (Big Data). Nowadays, everything is interconnected—computers, smartphones, watches, even your fridge, microwave, and the lights in your house. Different platforms receive this enormous amount of data and act like the quarries they use for mining.
In Big Data and Data Science, statistical practices, algorithms, AI, and ML are used to find patterns, trends, and explain why each of them (the patterns and trends) occurs in their respective contexts.
The Vs of Big Data
Volume
Does size matter? Here, yes. Massive amounts of data must be processed, and many factors come into play here, such as processing capacity and speed.
Velocity
This refers to the speed at which data is received and acted upon. In other words, we can think of it as the speed at which we take that data, process it, and turn it into something useful.
Variety
Variety speaks to the types of data available. There’s more of it, and it’s becoming more complex.
Value
Like oil, data has value, but we won't be able to monetize it without processing it properly. Many companies view data as a valuable asset.
Veracity
Finally, veracity speaks to how reliable the data we’re using is. Are you getting benefits from it?
How Can Big Data Help Us?
Have you ever wondered how Netflix suggests things you’re going to like? Simple, Big Data. Or for example, when you open Instagram and see an ad for a pair of pants that takes your breath away—yep, that’s also thanks to Big Data. Maybe in a few years, when microwaves or fridges are smarter, they’ll be able to know what your favorite foods are and how healthy you are based on the diet you follow and what you consume. They’ll also be able to suggest supermarkets with your preferred products and brands.
This is because Big Data helps companies improve their products, refine marketing strategies, and enhance customer experiences.
Continuing with the previous example, in that hypothetical case where your appliances are so advanced, supermarkets could minimize waste because they would know the product lifecycle. They’d have the data on how long it takes for you to consume items and go back to buy more. Maybe one of their cans of beans spoils too quickly because the packaging isn’t right, and this lets them improve the product to make it last longer. They might also notice a trend toward vegetarian diets, which would lead them to run ads related to vegetarianism and expand their product range for this type of customer.
Although this is something I’ve imagined for example’s sake, if the ultra-smart appliances become a reality, we would see a reduction in food waste, which would have a positive impact on society, especially in places where farming isn’t easy and people rely on seasonal produce. That’s the power of Big Data, and it’s just getting started. One of the biggest challenges is improving storage and processing capacity so that it grows at the same rate as the data, which doubles every two years.
Now, it’s your turn to imagine what wonders Big Data and a good team of experts can do for your business.
