{"id":64877,"date":"2023-05-26T20:10:38","date_gmt":"2023-05-26T20:10:38","guid":{"rendered":"https:\/\/mailrelay.com\/glossary\/big-data\/"},"modified":"2026-10-02T19:30:25","modified_gmt":"2026-10-02T19:30:25","slug":"big-data","status":"publish","type":"glossary","link":"https:\/\/mailrelay.com\/en\/glossary\/big-data\/","title":{"rendered":"Big data"},"content":{"rendered":"\n

Big data<\/em> is the process of working with huge amounts of data, beyond the capacity of conventional applications to capture, process and store that information in a reasonable time.<\/p>\n\n

That is why the concept of Big data involves infrastructures, technologies and services created specifically to manage this large amount of information and extract value from it in record time.<\/p>\n\n

1. What is Big data for<\/h2>\n\n

Big data is used to make relevant decisions based on the information previously obtained and processed according to our needs. This processing relies on various analytical methods to combine and isolate the information as reliably as possible. Big data can be applied to almost any field, here are some of its most common uses:<\/p>\n\n

– Comparative analysis.<\/strong> When customer behavior is known and can be observed in real time, it is possible to compare their current behavior patterns to identify opportunities.<\/p>\n\n

– Machine learning.<\/strong> Machine learning<\/em> uses Big data to develop automatic learning models for large amounts of data without the need for human intervention (or with minimal intervention).<\/p>\n\n

– Product development.<\/strong> Based on previous or current products, predictive models are created for new products and services through the classification of key elements.<\/p>\n\n

– Scalability<\/a> and failure prediction.<\/strong> Big data can anticipate problems before they happen by analyzing data (structured, unstructured or semi-structured) and fix them by focusing on the area where the problem is expected.<\/p>\n\n

– Customer experience.<\/strong> With Big data, information can be collected from multiple sources (social media, web browsing, mobile device use, etc.), all of which enables personalization and more efficient decision-making.<\/p>\n\n

– Fraud.<\/strong> The capabilities of Big Data to identify suspicious or unusual data patterns allows fraud detection and prevention.<\/p>\n\n

2. The 5 V’s of Big Data<\/h2>\n\n

To properly manage the huge amount of data handled in Big data, you need to know the five dimensions that make up Big Data, the so-called 5 V’s. They are:<\/p>\n\n

Volume<\/h3>\n\n

The amount of data generated is continuously increasing and as the databases grow, the applications and architecture built to support the collection and storage of data must grow\/evolve.<\/p>\n\n

Velocity<\/h3>\n\n

Immediacy is key, since data is generated at high speed and much of it will become obsolete in a short time, losing its value once more recent data is obtained.<\/p>\n\n

That is why speed of analysis is one of the fundamental characteristics of large-scale data management, and the increasingly complex algorithms must process information quickly.<\/p>\n\n

Variety<\/h3>\n\n

Since data comes from different places and scenarios (social media, mobile devices, proprietary architectures, etc.) and in different formats (images, video, text and audio), this variety makes collecting, storing and classifying it a challenge.<\/p>\n\n

Veracity<\/h3>\n\n

Knowing the reliability of the information collected is of vital importance, as it can be incomplete or come from sources that are not entirely verified (social networks). Therefore, depending on how this information will be used, effective filtering is of vital importance and provides a real competitive advantage.<\/p>\n\n

Value<\/h3>\n\n

The value dimension refers to the useful information that can be extracted from the data once it has been processed and analyzed. Generally, a large amount of data is needed to obtain a really small amount of valuable information. Value is the foundation of knowledge and this results in taking the right action or making the right decision.<\/p>\n\n

3. Benefits of Big data<\/h2>\n\n

After all this, you are probably asking yourself: but what are the benefits of Big data? Well, the truth is that there are several. The most notable ones are:<\/p>\n\n