Big data.

Organizations from different sectors increasingly depend on knowledge extracted from large volumes of data. It is crucial to know how to process data and transform it into information that becomes increasingly important to stay at the forefront.

The continuous increase in the volume and detail of data captured by organizations, such as from social networks, the Internet of Things (IoT) and multimedia, has produced an overwhelming flow of data, both in structured and unstructured formats (Hashem et al., 2014 ).

Big data is characterized by three aspects: (a) the data is numerous, (b) the data cannot be categorized into regular relational databases, and (c) the data is generated, captured, and processed quickly (Hashem et al. al., 2014).

Before the Big Data revolution, companies could not store all their files for long periods of time nor effectively manage huge data sets (Oussous et al., 2017). The increase in complexity and volume of data is making it difficult to apply big data analysis in the real world (Zhang et al., 2022). Big data has a complex nature that requires powerful technologies and advanced algorithms (Oussous et al., 2017). To extract knowledge from Big Data , several models, programs, software, hardware and technologies have been designed and proposed. They try to guarantee more accurate and reliable results for Big Data applications (Oussous et al., 2017) .

Some important points of Big Data for organizations:

· Data-based decisions;

· Analysis of trends and patterns;

· Improved customer experience;

· Operations optimizations;

· Innovation and product development;

· Risk management;

· More efficient marketing strategies;

· Security.

· Operational efficiency;

· Adaptation to market changes

Big Data plays a crucial role in the digital transformation of organizations, enabling them to make smarter decisions, innovate, improve efficiency and remain more competitive in a constantly evolving and competitive business environment, where information is valuable.