What is the definition of "Big Data" in data analytics?

The definition of "Big Data" in data analytics encompasses large volumes of structured and unstructured data. This concept illustrates the sheer scale and diversity of data that organizations generate, capture, and analyze. Big Data is characterized not only by the amount of data but also by its variety, velocity, and variability, often referred to as the "three Vs" (and sometimes more).

Structured data refers to information that is organized in a predefined manner, usually in databases, which makes it easy to analyze. Unstructured data, on the other hand, includes a vast array of resources such as text, images, videos, and social media posts, which do not fit into traditional data models. The ability to collect, store, and analyze such large volumes of diverse data enables organizations to uncover insights, make informed decisions, and enhance their strategies across various sectors.

Focusing on smaller volumes of structured data, high-speed data transmission, or data residing only in local databases does not illustrate the comprehensive nature of Big Data. These aspects do not capture the breadth and depth of all the information available, which is essential for effective data analysis in the contemporary landscape. Big Data is about leveraging vast and varied datasets to drive insights and value.