Big Data is extra-large amounts of information that require specialized solutions to gather, process, analyze, and store it to use in business operations.
Machine learning algorithms help to increase the efficiency and insightfulness of the data that is gathered (but more on that a bit later.)
Four Vs of Big Data describe the components:
Volume — the amount of data
Velocity — the speed of processing data
Variety — kinds of data you can collect and process
Veracity — quality, and consistency of data
How big is Big Data? According to the IDC forecast, the Global Datasphere will grow to 175 Zettabytes by 2025 (compared to 33 Zettabytes in 2018.) In case you're wondering what a zettabyte is, it equals a trillion gigabytes. IDC says that if you store the entire Global Datasphere on DVDs, then you'd be able to get a stack of DVDs that would get you to the Moon 23 times or circle the Earth 222 times.
Speaking regarding single Big Data projects, the amounts are much smaller. A software product or project passes the threshold of Big Data once they have over a terabyte of data.