Big Data is everywhere: from the series we watch on on-demand platforms and our activity on social networks to web browsing. The term Big Data refers to various information processing techniques that work with large volumes of data in real time.
This data allows companies to analyze all kinds of aspects related to consumer behavior and generate effective strategies to attract them and increase sales.
These data sets have specific characteristics known as the “V” of Big Data:
Volume. This refers to large volumes of data that can come from different sources: history of interactions on a website with thousands of visits, logins to portals, access to mobile apps, data generated during sales processes, among others. Big Data analyzes volumes of up to petabytes (1,000 terabytes).
Variety. Big Data data is heterogeneous: since they do el salvador whatsapp number database not all have the same characteristics, they cannot be processed in the same way. For example, analyzing written information is not the same as analyzing images or other multimedia content. To perform this task, tools such as ERP or CRM are required.
Velocity. Velocity refers to how quickly data is created, stored, and processed. This data can be structured and easy to manage, such as data from databases, or unstructured, including videos, images, social media posts, clickstreams, and more.
Variability. In Big Data, this concept has two meanings: on the one hand, the number of inconsistencies in the data; and on the other, the diversity of data dimensions.
Volatility. Given the speed and volume of data, volatility must be considered. Rules for the availability and currency of information are needed.
Veracity. Refers to the origin or reliability of the data source, its context, and how important it is to the analysis.
These data come from a variety of sources. Some of them are:
People. They share their data by filling out forms, interacting on social media, sending emails or replying to a text message.
Machines. A GPS, a Wi-Fi network or an electric energy meter also generate data that can be analysed.
Biometric statistics. These come from security systems and can be fingerprints, facial or voice recognition.
Data transaction statistics. These are data generated from online purchases, electronic money transfers, online reservations, etc.