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📈 #34 The third wave of analytics

📈 #34 The third wave of analytics

Where are you going to be when it explodes?

Borja Menéndez's avatar
Borja Menéndez
Apr 14, 2024
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📈 #34 The third wave of analytics
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It was 2010 and Eric Schmidt, CEO of Google, said that "every two days we create as much information as we had created from the dawn of humanity up to 2003."

That's saying a lot. Like 5 exabytes of data. Or 5,000 petabytes. Or 5,000,000 terabytes, in case that resonates more with you. Quite a feat, really.

But it keeps growing. If we look at it in zettabytes (each zettabyte equals 1,000 exabytes), it's projected that by next year there will be around 181 zettabytes created across the entire planet Earth.

So I look at it and wonder, "What do we do with so much data?"

Well, analytics, of course. Improving business processes. Understanding what has happened, what will happen, and how it should happen.

And for that, Operations Research is crucial.

That's why, today in Feasible, I tell you all about analytics:

  • The existing maturity in businesses.

  • The one that already exists in technology.

  • And how the market is increasingly demanding experts in OR.

So let's go for it!

💼 Business Maturity

You've probably seen the following image on more than one occasion.

It's an image that summarizes the complexity and level of intelligence that each type of analytics brings to a business.

You'll also see that sometimes other types of analytics are included, but these three are the ones that 🏅 take the cake:

In reality, everything starts with data 📊. The more data that is collected in an organized manner, the better for a company.

I remember back in 2012, while doing my Final Year Project, I met a guy who was dedicated body and soul to Big Data. I must admit I didn't understand it very well, but he was passionate about it ❤️. And I also remember that it was quite a peak moment for Big Data, data processing and organization, the boom of ETL processes (Extract, Transform, Load)...

There was also a rise in descriptive analytics 📉, which is dedicated to summarizing and interpreting historical data to understand well what has happened in the company.

How? Through data visualizations or analysis of historical trends 📈.

Always with the goal of enabling data-based decision making. This was the starting point for analytics in business. In fact, today this is the core of any business report.

But of course, businesses always want to go a step further. If they have managed to understand the past through data, why not try to predict the future? 🔮

That's where predictive analytics comes in, that is, everything that has to do with Machine Learning 🤖. And if before what we wanted was to know what had happened, now what we want to know is what will happen in the company.

With technologies like Machine Learning, by looking at past data we can try to foresee the future to find growth opportunities 🚀.

But if we already have an idea of what will happen, how can a company take the necessary steps to get there? That's where prescriptive analytics comes in, which tells you how it has to happen.

The ultimate benefit of a company using prescriptive analytics is huge, as it enables decision-making teams to better understand what to do and how to do it before making the decision, saving both time and money in applying the best possible option for their business 💡.

With this, they take data-based decision making to its highest expression. They not only understand what has happened and what could happen, but they know what steps they should take to get there.

This is the point some companies are already at, but there's still much to be exploited here.

All these business needs have strongly driven a maturity in technology 👇🏻.

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