What Is Big Data? Why Is It Important Today?

What Is Big Data? Why Is It Important Today?

If you had no idea what is Big Data, you are starting to suspect it. But you don’t need to be a professional involved with IT to enjoy or even know what it is and how it interferes decisively in many areas in which we are directly or indirectly involved.

What Is Big Data?

As in most cases related to IT, in which almost all nomenclatures use the English language, the literal translation may or may not explain ​​what it is about. In this case, the translation means “big data” or, for those who already have at least a notion of what it is, a big database.

However, this is a case where just translating does not define what it is. First, data size alone is not the only requirement to classify something as eligible for the category. Also, what is great for some may not be so great for others. Some aspects are added together, and requirements are met, making a dataset/information assume this condition or classification.

Containing a large volume of data is a prerequisite, but not the only one. How much the volume of data grows over time, that is, the speed at which this happens, the nature and diversity of the data and how it can be categorized, the authenticity of the information, or how secure it is in terms of reliability, as well as the relevance it has to produce scenario switching, are other factors that are normally considered.

Data Volume Growth

You can have a gigantic database that includes absolutely everything your company has done over the decades of existence. For that reason, it is natural that the volume is large. But suppose over time, the growth of this data – as a result of the inclusion of sales, billing, inventory, expenses, revenues, and all kinds of organizational data – little affects the total volume and, above all, the nature of this data. In that case, we cannot classify this data. 

If, on the other hand, the volume of new information added to what you already have is representative in total terms, in such a way that it can change the general profile of this data, we can admit that another fundamental condition has been met. The bank is eligible to be it. Can you imagine the volume and rate of data growth that Google and Facebook have daily? These are extreme cases, but that’s more or less what we’re talking about!

Nature And Diversity Of Data

It is important to understand that the modern world and existing technologies produce large volumes of data and how the nature and diversity of this data change and is even unprecedented in many cases.

In the recent past, databases were meant to store only text and numbers. And even such readable data could be classifiable into narrow, well-defined categories. There was no doubt or difficulty for anyone who modeled a database on how to classify billing or inventory tables.

But what about extremely dynamic and variable content that comprises a personal profile on a social network like Facebook? People post texts, images, videos, and who knows what else is coming soon! How do Facebook and any company that deals with this reality categorize every piece of information published by its more than 2.3 billion users?

This is a clear example of the nature and variety of data, which requires new approaches to storing, organizing, manipulating, and interpreting information to be useful in decision making.

Information Authenticity

To define authenticity is to define that you are yourself and not someone else. In terms of data, it’s the same thing. Is there security regarding data integrity? Is the source providing the data secure? Has the data not been manipulated or altered?

It is to ensure, by all possible means, that the feeding of the collected data is surrounded by mechanisms that can guarantee that the data are reliable; that is, they are faithful. They are not susceptible to the collection, transmission, and categorization errors for subsequent storage. More than that, they are not tamper able by any means. The concern about this is understandable, as false data, even if slightly altered, can mean wrong conclusions. Want an example? Imagine that 

Information Relevance

All information stored in a database, even the simplest, must have importance; that is, it must meet an end, a purpose, an objective. Simply storing data without it is worth anything creates a “database.”

And don’t you think this is unusual. On the contrary, the evaluation of many databases destined for the most diverse purposes reveals that much of the stored information has no destination. In some cases, they are insensitive data or that cannot change any analysis made of them.

Therefore, the information must be capable of modifying, altering, revealing things, and being valid to a greater or lesser extent for someone or some decision-making. A real example, still using the launch of the probe by NASA, knowing that on the day planned for the launch, there will be a solar storm, is data of high relevance for the mission’s success.

How Does Big Data Work?

This is not a question that can be answered in a way that meets all realities. Currently, it can be a simpler or more complex solution, even if what is considered simple is not so much.

Some factors are part of a data solution, which means heavy investments, whether on the financial side of the technology involved. The plural is correct, that is, technologies.

The first point of a infrastructure refers to the data itself. For this, it is necessary systems that properly collect the data and that there is infrastructure (hardware and software) to store them, normally making use of storage, which are servers specialized in storing large volumes of data and that depending on the size of the solution, can take up a lot of space in data centers.

Also Read: All You Need To Know About Big Data

Techno Team

We are a power packed team of cults who love to explore new technologies and bring all latest news to our viewers.

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