Technology has influenced so much in our lives. However, most people don’t think about the vast amounts of data they generate every time they answer the phone. However, the importance of this information does not escape businesses. That is where big data analytics comes in. Increasingly, digital technology is seen as the basis of any entity that wants to develop its business successfully. As a result, companies attract rare data scientists with diplomas from schools and organizations that offer digital training. So what is big data analytics? You can read about it in the article below.
Big data technologies have enabled use cases that were previously impossible due to large amounts of data or complex analysis. Now, leveraging big data visibility helps many businesses deliver personalized and superior customer service, achieve greater efficiency, lower prices, and a sustainable level of service, and even allow healthcare organizations to leverage petabytes of patient data to deliver high-quality medical services. Of course, data is one side of the coin, but the other important aspect is the ability to analyze big data. But let’s start from the beginning, i.e., the definition of big data.
What is big data?
The term means large sets of data or vast amounts of data. These are such extensive collections that no conventional database or information management tool can work. Indeed, we create trillions of bytes of data every day. It’s information from everywhere: news we send, videos posted, weather info, GPS signals, online purchase transaction records, and much more. This data is called big data or vast amounts of data. Network giants such as Yahoo, Facebook, and Google were the first organizations to start using BD technology for their business.
However, delivering an accurate or universal description of big data is difficult. It is an elaborate concept, and the definitive meaning may differ depending on the type of end service user or provider.
Big data analysis
Big data analysis is a comprehensive study of a set of information to draw conclusions that allow a company or other entity to make a decision. That means that we refer to examining and interpreting a database to solve a problem or find answers to questions. During this analysis, data may be exchanged, for example, to obtain statistical indicators. Note that this is the data analysis process that follows information gathering. Therefore, it follows that the BD analysis covers all the tools that we can use to study the database, including visualizations such as, among others, histograms, bar charts, and pie charts.
Big data is hard to imagine. It is impossible to process either by a human or an ordinary computer. Big data analysis is a solution designed to allow anyone to access these gigantic databases in real-time and enable the choice of conventional database and analytical solutions. This idea involves a family of instruments corresponding to three elements, called the 3V rule.
• Volume – a large number of data; the more data there is in the set, the greater the significance of the information obtained
• Velocity – high variability of data; the system must process data in a short time to provide relevant information in the shortest possible period
• Variety – large variety of data; data should be obtained from various sources
In recent years, however, more and more talk about two additional elements, and thus the 5V concept. Additional rules include:
• Veracity – credibility refers to the reliability and credibility of the information collected. As BD contains an infinite amount and many forms of data, it isn’t easy to justify the authenticity of content, but analysts are in the operation of designing new strategies that should enable the managing of this type of data
• Value – the concept of value corresponds to the profit obtained from the use of big data
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Types of big data analysis
Data analysis can be of two types:
• Quantitative: The information is numerical, against which you can compile accurate statistics. For example, grades obtained by class students in the last semester.
• Qualitative: This is information extracted from a database, usually presented in textual form. For example, a target audience in which participants were asked to give their opinion on a new product.
Data analysis tools
Various tools from fields such as statistics, econometrics, and mathematics are used to analyze the data. For example, we can use statistical metrics such as mean, standard deviation, or median to get information about the behavior of a variable. For its part, econometrics provides us with essential tools such as regression analysis. In this sense, we can also use graphics that provide visual information, for example, from a histogram. Nevertheless, we should mention that data analysis is not without limitations. First, that is because variables are difficult to quantify with precision. Next, that is why probability is often referred to in data analysis.
The usefulness of data analysis
Data analysis can have different uses for companies and state or non-profit organizations. For example, a country aiming to reduce child malnutrition in a country will continuously evaluate the rates of childhood anemia within a specific age range. Likewise, the company can analyze the satisfaction data displayed by its customers after a survey of all people who used their services in the previous month. This way, you can make decisions about your trading strategy.
We will measure the big data market in hundreds of billions of dollars in a few years. That is the new El Dorado for business. Many BD applications are still being improved, and in the coming years, we can expect new applications that we do not expect today. In a way, Big Data is a turning point for organizations that are at least as necessary as the internet in its time. Data analytics becomes vital in the era of big data, i.e., data sets so large that they exceed the capabilities of traditional computer applications to process them in a reasonable time. Therefore, companies must start implementing big data analysis to stay competitive and increase their profits.