Big data refers to extremely large and complex sets of data that are difficult or impossible to process and analyze using traditional data processing tools.
The term is often used to describe datasets that are so large and complex that they cannot be handled by traditional data management and analysis software.
Big data can be found in various forms, such as structured data in databases, semi-structured data in log files and social media, and unstructured data such as text and images.
The three main characteristics of big data are volume, velocity, and variety. Volume refers to the large amount of data that is generated, collected, and stored.
Velocity refers to the speed at which the data is generated and needs to be analyzed. Variety refers to the different types of data (structured, unstructured, etc.) that need to be analyzed.
Big data can be used to discover new insights and hidden patterns in the data, and can provide organizations with a competitive advantage by enabling them to make better decisions and improve their operations.
Big data is used in many fields such as healthcare, retail, finance, and transportation to improve the business process, making predictions, and gain insights.
There are various technologies that are used to manage and analyze big data such as Hadoop, Spark, and NoSQL databases, which enables to store and process big data in parallel, in distributed systems and with more cost-efficiency.