The phrase "amount of data produced" is correct and usable in written English.
It can be used when discussing the quantity of data generated in a specific context, such as research, technology, or business analytics.
Example: "The amount of data produced by the new software has exceeded our expectations."
Alternatives: "volume of data generated" or "quantity of data created."
Today, the amount of data produced is massive, and it increases exponentially with time.
It can be effectively used to understand the large amount of data produced during software evolution.
If it does, the enormous amount of data produced in the wake of the Human Genome Project could find a common language on the Web.
It can be effectively used to analyze and understand the large amount of data produced during software evolution.
This technique provides even more structural information, but at the cost of doubling the amount of data produced for each experiment, further increasing our big data challenges.
In recent years, the amount of data produced has been exploding at a rate far greater than the increase in computing power of even large supercomputers.
The increasing amount of data produced by large-scale biological experiments has highlighted the inadequacies of traditional scientific data management methods such as laboratory notebooks.
The compilation of the large amount of data produced during experiments is one of the key tasks to address in radioactive ion facilities.
Learn about how the Internet of Things and the huge amount of data produced by connected objects is leading to better design and a continuous improvement loop, changing the design process and leading to better tools for building better products.
Currently, techniques exist to compute buffer capacities that guarantee satisfaction of the throughput constraint if the amount of data produced and consumed by the tasks is known at design-time.
The only way one can gain insights from the vast amount of data produced from next-generation sequencing is by applying artificial intelligence and pattern recognition — no human being can process so much data.
