Big data is the term used to refer to the huge amount of data and information that's generated these days. But not only this. When defining big data, we're also talking about how this data and information is captured, stored, extracted, analyzed, categorized, queried, shared and updated. It's a broad concept and one of the most relevant topics in the technology market. After all, big data interferes with the routine and life of us all.
But why do we talk so much about big data? The best answer to this question is that this huge amount of data and information can be used to solve issues and problems that couldn't be resolved before. That is, big data acts by providing subsidies so that processes, technologies, and companies can develop, evolve. Just imagine how analyzing disparate and seemingly disconnected data can detect security breaches, illnesses, and even new business opportunities.
Just to get an idea of all this, according to the research firm IDC, the global data sphere will almost triple from 2018 to 2025, from 33 zettabytes to 175 zettabytes. Can you imagine that? It's insane.
“Data is at the heart of digital transformation, the lifeblood of this digitization process. Today, companies are leveraging data to improve customer experiences, open new markets, make employees and processes more productive, and create new sources of competitive advantage – working toward the future of tomorrow”, says the company's report, The Digitization of the World, from 2018.
How big data works
Of course, the practice of capturing, storing, and analyzing data isn't new. But with so many devices plugged in and delivering data all the time, such as smartphones, tablets, laptops, and televisions, we had never talked so much about big data as now. Nevertheless, for almost 30 years the subject has been discussed. Even the use of the term big data is credited to the computer scientist John Mashey, who began using the word in the 1990s.
As might be expected, the concept of big data has changed over time, keeping pace with technological developments. But it’s undeniable that it still has links with at least 5 important characteristics.
Volume is a big data feature that refers to the large amount of information and data that's collected and stored in diverse sources. In general, the more data the better. After all, we assume that more data can generate more insights and better results.
Variety refers to the format, type, and nature of the data. For example, they’re video, text, image, audio, number, samples, etc. Undoubtedly, the greater the data variety, the more likely processes evolve and new ideas emerge. But of course, on the other hand, a greater variety of information also brings a huge complexity of analysis.
Velocity is a big data characteristic of how fast data and information is generated, processed and updated. There’s no point in having a large volume and variety of data but no processing speed. After all, when we talk about big data today, we’re practically talking about information and data that travels in real time.
Value refers to the quality and importance of the data. In other words, the information needs to have quality and mean something productive for the company. Otherwise, if they don't help the company, don't contribute to the development of the business, it's better that they’re discarded.
Veracity is the characteristic of big data that refers to the reliability of the information. Can the company really trust these data? Unfortunately, we live in the age of fake news and cyber scams and attacks. Therefore, veracity ends up being an important feature of big data.
Big data and cybersecurity
It's unthinkable to talk about big data and not talk about cybersecurity and information technology. It would be a shame for us, a digital security company. I say this because, over the years, big data has proven to be a great ally in fighting threats and cyber attacks.
In this context, big data has mainly helped to improve cybersecurity solutions. How? For example, helping to reduce the time of threat detection, to evaluate better the risks of data breaches, and to solve other types of problems.
Here at Gatefy, we combine big data with artificial intelligence (AI) and machine learning (ML) in our email security and protection solutions. The result is a more powerful and assertive protection tool that has the ability to absorb data and information and learn from it. It's an evolution in threat detection and blocking that takes into account the automation and the simplification of processes and operations.
If you would like to discuss this further, please contact us: email@example.com. We'll enjoy talking more about big data.