BigQuery can speed up querying large datasets, but its impact on data science depends. While it's efficient for basic SQL-like functions, complex data processing may require methods outside BigQuery. Transferring data to Python environments like pandas can be slow due to limitations in existing libraries like google-cloud-bigquery and pandas-gbq. So, while BigQuery offers advantages, consider its limitations and the efficiency of data transfer when integrating it into data science workflows.

I recommend checking out this article medium

This isn't really a discussion type question and will be likely better answered via research. There's a LOT of information available about BigQuery; how and where it's used, advantages as well as how it's relevant to data science. Some research on the internet will likely provide a wealth of information. I would start at the main website BigQuery and even this very specific article about using BigQuery for data analysts and data scientists.