Google Cloud Platform Tools for Data Science Part 1: Data Processing and Databases
With the ever-growing volume of data generated daily, it’s essential to have the right tools and infrastructure to store, process, and analyze this data effectively. Enter Google Cloud Platform (GCP) — a suite of cloud computing services and tools designed to help users quickly solve complex business problems. Using GCP tools like BigQuery, Dataprep, and BigTable has improved my workflow as a data scientist and I have just scratched the surface of what’s possible with this awesome suite of tools.
In this article, we’ll explore the powerful data science tools provided by GCP, and how they’re being used to drive insights and innovation in modern data science. I’ll introduce each tool and give examples of how and when to use it, starting with the tools for Data Processing and Database Management. Hopefully you’ll learn something cool or be inspired to try out some new tools for your projects!
Data Processing Tools
Data processing is a crucial aspect of data science that converts raw data into usable data. It involves several steps, including data collection, cleaning, transformation, and…
