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What is the meaning of Big Data? This expression is increasingly common on networks and in companies, and has become an important characteristic of Industry 4.0. With the advancement of technology and information systems, data is essential today for various sectors, whether in administrative, process, marketing, or production terms. The literal translation of Big Data in Portuguese can be understood as a large amount of data (in the sense of stored information). Let's better understand what this means, as well as the importance of Big Data, the 5 Vs of Big Data, and some examples of Big Data. Happy reading! ALSO READ: • Do you know what neural networks are?
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What is Big Data and why is it important?
Before understanding the meaning of Big Data, let's understand what Data means. The quantities, characters, and symbols used in operations performed by computers, which can be stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media, are "data". Big Data is a combination of structured, semi-structured, and unstructured data collected by organizations, which can be mined for information and used in machine learning projects, predictive models, and other advanced analytics applications. Systems that process and store Big Data have become a common component of data management in organizations, supported by tools that assist in their analysis. In short, Big Data refers to immense amounts of stored data, whose importance lies not only in what this data represents, but in how it can be used. Its analysis allows decisions to be made with greater precision, providing confidence when taking strategic actions in the industrial and corporate sectors.
What are the 5 Vs of Big Data?
In seeking to understand the meaning of Big Data, it is important to analyze the five Vs of Big Data. Check them out below: • Volume: If we think of Big Data as a pyramid, volume would be the base. The volume of data that companies store has grown to unprecedented levels since 2012, and the volume has been increasing ever since; this immense amount of data is what gives the "Big" to Big Data;
• Velocity: in addition to managing data, companies need this information to flow quickly, preferably in real time. Sometimes velocity is more important than volume because it generates a competitive advantage; therefore, it may be better to have a smaller amount of data in real time than a larger amount at low speed;
• Variety: a company can obtain data from different sources, such as electronic devices and sensors, or through what people are posting on social media; the importance of these sources varies depending on the business niche or industry;
• Veracity: in this context, veracity is equivalent to quality; a company may have the data it searched for, but it must check if there is anything missing, if the data is accurate and "clean", and if there is a use and purpose in its application;
• Value: moving up the pyramid, we then reach the top, which is value; value refers to the ability to transform an immense amount of data into business. This is where the application of Big Data is executed.
What are the examples of Big Data?
We understand the meaning of Big Data, and now we move on to its application. There are several examples of Big Data, with useful real-world applications that make a difference in how companies can manage their business and make decisions with strategic quality and informational precision. We have listed below some examples of Big Data: • Transportation: Big Data powers the GPS applications we use on our devices, necessary for us to get around the local urban area; GPS data sources include satellite imagery and government agencies. Airplanes generate large amounts of data for transatlantic flights. In the transport niche, Big Data serves to manage congestion and traffic control, as well as route planning, for example;
• Advertising and Marketing: in the past, marketers analyzed television and radio and conducted focus group surveys to find out how the audience would respond to certain marketing strategies, a process that was costly and time-consuming. Today, it is possible to collect large amounts of data to identify what consumers click on and search for much faster; the goal is to know what potential customers "like" and what that represents for the industry;
• Financial and banking services: the financial industry uses Big Data for various purposes, such as fraud detection (analyzing purchasing patterns and anomalies in customer behavior), risk management, customer relationship optimization, understanding better how to prospect consumers and encourage the use of financial products;
• Media and entertainment: the entertainment industry is one of the examples of Big Data, and uses data to analyze consumer opinion, predict market interests and preferences, optimize its programming and its marketing campaigns. Two examples are Amazon Prime, which uses Big Data analytics to recommend shows to users, and Spotify, which does something similar, offering personalized music suggestions;
• Meteorology: satellites and weather sensors around the world collect large amounts of data to track environmental conditions. Meteorologists use Big Data to study patterns in natural disasters, make weather forecasts, understand the impact of climate change, predict the availability of drinking water in regions and issue alerts for critical events such as hurricanes and tsunamis;
• Healthcare: Big Data is also present in the healthcare industry. Here, devices and sensors can collect patient data, which is transmitted to individuals' electronic health records. Organizations can then use Big Data to predict epidemics, prevent diseases, issue real-time alerts, accelerate research processes, etc.
Other examples include the use of data in cybersecurity and education, which demonstrates the importance of Big Data, and how it has spread to all niches of modern society, from consumers to businesses, from the scientific field to services.
Conclusion
The meaning of Big Data encompasses a massive set of content (data) collected with some objective, which can involve terabytes, petabytes, and even exabytes. This technology is one of the greatest innovations of the digital era. Through in-depth analysis, collecting data on this scale provides vital information for decision-making and planning methods in almost every type of industry. In the last decade, Big Data has grown to the point of being present in almost every aspect of our lifestyle, involving our consumption habits and individual preferences. Finally, Pix Force offers several technological solutions based on Big Data. Get in touch with us and learn more!
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
