Big data is the term used to describe extraordinarily vast and varied sets of semi-structured, unstructured, and organized data that keep growing rapidly over time. Conventional data management systems are unable to store, handle, and evaluate these datasets because to their enormous size and complexity in volume, velocity, and variety. 

AmountThe volume of data is important. Processing large amounts of unstructured, low-density data is necessary when working with big data. Clickstreams from a website or mobile app, sensor-enabled devices, and X (previously Twitter) data feeds are examples of unvalued data. This might translate to tens of terabytes of data for certain firms. It could be hundreds of petabytes for others. 
SpeedThe quickness with which data is received and (perhaps) processed is known as velocity. The fastest data typically flows straight into memory rather than being written to disk. Certain smart devices with internet connectivity function in real time or almost real time, necessitating immediate assessment and response.
Variety The different forms of data that are available are referred to as variety.

Extremely large and diverse collections of organized, semi-structured, and unstructured data that continue to develop quickly over time are referred to as "big data." The massive quantity and complexity of these datasets in terms of volume, velocity, and variety make them impossible for conventional data management systems to store, handle, and analyze.
Big data, artificial intelligence, machine learning, and other advanced technologies are studied in data science. The system analyzes vast amounts of structured, semi-structured, and unstructured data to derive insights and meaning. Based on these insights, a pattern can be created that can help with decision-making related to seizing new business opportunities, improving products and services, and supporting business expansion. Utilizing data science techniques to interpret massive volumes of data.

Social media: Currently, a sizable portion of the global populace uses platforms like Facebook, Instagram, YouTube, WhatsApp, Twitter, and WhatsApp. Every action you take on these kinds of media—uploading an image or video, messaging someone, leaving a remark, like something, etc.—creates data. 
A sensor positioned differently: A sensor that collects data on temperature, humidity, and other parameters is positioned across the city. A camera positioned next to the road collects data and gathers information on the flow of traffic. A lot of data is generated by security cameras installed in high-risk locations like airports, train stations, and retail centers.

IoT Appliances: Internet-connected electronic appliances, such as smart TVs, washing machines, coffee makers, air conditioners, etc., generate data for their intelligent features. It is machine-generated data, produced by sensors housed in different kinds of gadgets. An instance of this would be an internet-connected smart printing device. These printing devices can exchange data among themselves when they are linked to a network. Thus, if a file copy is loaded into one printer, the content of that file is stored by the system so that it can be printed out in hard copy on a different printer located on a different floor or in a different building. Data is produced by this kind of data communication between different printing machines. 
E-commerce: In business, banking, stock market, and e-commerce transactions,