The importance of Big Data Analytics and Machine Learning

…, and why you need to learn more about it.

Many data, but for what?

In summary, big data is the large structured or unstructured volume of data that inundates our world every day, every time, every moment. But it is not the mountain of raw data that is important. It is what organizations do with the data that matters. Big data analytic is used for insights that lead to better ways, making decisions to move the business to the next level.

Now we are going hands-on and understand how it works.

Data x Information x Knowledge x Intelligence

Imagine that a company has a table with the employees' information: salary, name, age, and role.

The age is a single data, and it is not important for anything. When we associated many data, like name, age, salary, and role, we have information.

In this example, we can see that John is 20 years old and earn 6k per month working as an analyst. John has a manager called Max, and he earns 10k per month. If John wants to earn 10k when he turns 30, what is the probability to become true? May Max retiring when he turns 55? Or will the company grow sufficiently to have 2 financial managers in 10 years?

Do you understand how the information matter for a decision? It is knowledge.

Well, it is missing the intelligence. Imagine the following situation:

5 people grow up in the same city, studying in the same school. Suppose that all of them have an identical environment do a challenge: break a wall. Remember, these people have the same brutal force, the same intellectual knowledge. 2 of them will break the wall easily, 1 need more time to do it, and 2 people can not break the wall. Why some people can do it and others not?

The difference is the way that these people use all of their knowledge and the associations that they use in your brain to solve this case. It is called intelligence, the ability to make a decision using our own knowledge.

A good example is the people that grow up in the same city, attending the same university, but go on in a different course. They use the knowledge of different forms, to get different things.

Different ways.
Different ways.
Different ways, same origin.

In a short definition, big data analytics is to extract knowledge from a lot of data/information, using intelligence to make better decisions.

The perfect storm.

… and why Big Data Analytics is so important.

  • We have exponential growth of data volume in the world, by multiple channels: Facebook, Twitter, Whatsapp, Google, Google Analytics, Clicks, Posts in blogs. We have more data in the last 2 years in comparison with all of human history;
  • Low price for storage. HDs, SSDs, Cloud Storage, for a few dollars;
  • High computing capacity, processing more information in less time.

Data is the fuel of Business Intelligence (the past) and Predictive Analyze (the future).

And if we learn machines to use intelligence?

Machine Learning is the technique to use algorithms with intelligence, namely, using the machine to solve many problems with a heavy computer capacity.

Data centers are a simple way to have high-performance computing,

We are living in the age of data explosion and we have many resources to explore them. The future is instructed to data.

Ok, I understood now whats is these terms. But why is it important to?

Go ahead again and explain better why Big Data Analytics and Machine Learning matter.

Descriptive and diagnostic analysis are used in Business Intelligence to understand the past, using all the old information to justify the actual scenery and think about how to improve something. Well, but what about the future? We could analyze the future using past information, but it is inconclusive, in a no-good precision level.

Today it is perfectly possible thanks to the constant evolution of analytics systems, enabling predictive and prescriptive analysis with a guarantee the precision of these studies.

Knowledge makes us smart; people and companies learn. And now machines learn with us.

This is a simple definition, and I hope you enjoyed it.

I am enthusiastic by Cloud and in-house computers, with a passion for BI and ML. • Azure Solutions Architect Expert, Microsoft Solution & BI Specialist.

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