Big Data – its Importance and Management

Source: Pixabay

After the outbreak of the COVID-19 pandemic, the importance of storing and managing online data has become one of the main priorities of the modern era. The enormous amount of devices connected to the Internet means the constant and real-time generation of incredible amounts of data, which, once analyzed, will become statistical reports, predictive models, and new algorithms capable of detecting and anticipating behavior patterns of online users.

What is Big Data?

By definition, Big Data is a set of data of great variety, which are generated in large volumes and at an ever-increasing speed. Big Data is generated through many of the activities we carry out on a daily basis, therefore, the data sources are truly diverse: GPS devices, facial recognition sensors, and social media are just a few examples. Most people use some kind of technology or online services like Gmail or Facebook. These companies allow us to send and exchange data and, in return, use the data that we provide them with. In other words, online services, websites, apps, and many other devices are constantly analyzing data to make their services more efficient and to develop new products. And for this, they use Big Data tools and services (such as Hadoop or NoSQL) to analyze and process massive data in order to improve their offer. In addition, Big Data analysts who hold certifications such as the Big Data Hadoop analyst certification in Madrid, also tend to be trusted in finding suitable and applicable solutions as the following sections will reveal.

The Importance of Big Data

What makes Big Data so useful for many companies is the fact that it provides answers to many questions that companies didn’t even know they had. With such a large amount of information, the data can be shaped or tested in any way the companies consider fit. The main purpose of Big Data is that it allows access to more information. And the more information you have, the better you can make decisions or find solutions. In many cases, the data analysis process is fully automated, which means, such advanced tools are available that they create millions of simulations to obtain the best possible result. But to achieve this with the help of analytical tools, machine learning, or even artificial intelligence, you have to know how big data works and configure each element correctly. This is why data scientists need a well-thought-out system to manage Big Data, with sufficient capacity to support all the necessary processes.

Possible Setbacks

There are three types of data: 1) unstructured data types: documents, videos, audios, etc. 2) semi-structured data types: software, spreadsheets, reports 3) structured data types. Only 20% of the information is structured and that can cause many errors if we do not undertake a data quality project. It is difficult to collect, clean, integrate and obtain high-quality data quickly. It takes a long time to transform unstructured types to structured types and process all that data. The data changes quickly and that makes them have very short validity. To solve it we need very high processing power. If it is not done right, processing and analysis based on this data can lead to erroneous conclusions, which can lead to errors in decision-making.

Quality and Reliability of Big Data

In 1987 the International Organization for Standardization (ISO) published the ISO 9000 standards to guarantee the quality of products and services. However, the study of data quality standards did not begin until the 1990s, and it was not until 2011 that ISO published the ISO 8000 data quality standards, but they need to be refined. In addition, research on the data quality of big data has only recently started and there are hardly any results. The quality of big data is key, not only to be able to obtain competitive advantages but also to preventing us from making serious strategic and operational errors based on erroneous data with consequences that can be very serious. Online safety has become a top priority, not only when it comes to big data analysis, but also when performing any online activity. For example, at ArabianBetting safety is crucial, as they only hire people who have experience in online games of chance themselves and know exactly what to look out for. They educate and provide online gambling reviews and what also should be avoided, as well as the factors that contribute to a high-quality sports betting site.

In conclusion, the quality of big data has become the key factor for data processing and analysis, but it is still in process of becoming truly reliable.