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The market for Big Data is in full expansion. Although the need to transform data into information for decision making is not new, the implementation of Big Data in many areas of large companies has made visible the importance of data as a strategic resource.
Therefore, for companies that are digitally transforming their organizations, Big Data is already a crucial resource to meet the challenges of the future. Because, without a doubt, the future belongs to companies that understand how to collect, store and use their data effectively.
The key to Big DataThe key to success, therefore, lies in the useful information that companies are able to extract from the data collected. Because having a lot of information and not knowing how to use it is of no value. That is why companies need new tools and technologies to manage these huge amounts of data in order to get the maximum potential out of the data they have. This translates into the need to hire personnel to facilitate the integration of Artificial Intelligence solutions for the management and automation of Big Data.
Although the implementation of Big Data, due to the high economic investment it requires, is being carried out mainly in large multinationals, more and more SMEs are incorporating Big Data analysis and management because of the competitive benefits it brings them. In these cases, the work is usually outsourced through cloud services, which are the most demanded. Cloud-based data analysis helps to reduce the costs of storing large amounts of data.
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Any device that is capable of storing and processing information is a source of data. So the most important thing is that from the raw data, it can be organized so that it can be converted into useful information for businesses.
In this sense, Big Data makes it possible to collect information from website visits, social networks, call logs and other data sources.
Big Data is a term that refers to large volumes of data or big data that require computer applications, based on Artificial Intelligence, for their proper processing and that allows transforming the information generated into a company's asset.
In this way, decisions can be made from a more realistic perspective (about what is happening) and not just based on intuition. This allows, for example, a company to launch products and services aligned with the needs and desires of its customers in a given time period.
In this sense, understanding customer trends and decisions helps guide a company in the direction it should take.
The 3 classic magnitudes that define Big Data are known as the 3 V's: volume, variety and velocity.
Likewise, Big Data can also be defined based on the measurement of other complementary magnitudes that we list below:
Every time a person visits a website or accesses a social network from their smartphone or laptop, they are leaving a trail, providing a series of data about their online activity and how they interact with products or services.
By using technology to manage Big Data, a company will thus be able to get to know the user (new, potential or established customer) in depth and delve into their needs, frustrations and desires in order to generate satisfactory user experiences. It also offers the opportunity to segment customers according to their preferences.
In its beginnings, Big Data was developed only in communication and marketing companies, but thanks to the evolution of technologies and the market itself, there are many sectors where it is being successfully applied, such as sports, commerce, security, medicine or transportation, with the aim of improving the interaction experience, as well as optimizing the value offered to the customer in order to build customer loyalty.
Big Data can be used to manage and optimize countless tasks in companies, among which we can highlight:
The information analyzed by Big Data can come from a multitude of sources. The most frequent sources due to the quantity and quality of the data they offer are the following:
The use of Artificial Intelligence in business is becoming more and more common and necessary for the optimization and evolution of processes. In one of our [...]Read More »