Google Cloud Platform (or GCP), a Google service, is a cloud computing service that Google originally developed internally and then rolled out for public use. The same infrastructure powers Google’s internal tools and services along with functional support for data storage, analysis, and application development. The service was launched for application developers in 2008 and has steadily expanded its offerings since that time.

Some critical features of GCP include the following:

• Compute services powered by App Engine, Compute Engine, and Kubernetes
• Data warehousing in Google Cloud Storage, Google BigQuery, Google Cloud SQL, and others
• Machine Learning services such as AutoML, Translation API, Vision API, and others

We here at Data Courses focus on using GCP for our tutorials due to the ease of setup for many analytics purposes detailed in our tutorials. Topics we cover and plan to cover, include using BigQuery to store and load data for analysis, using Google Cloud Functions to build small analysis functions in the cloud.

GCP has been useful for the contributors of this blog for additional services such as the development of scientific applications using Python’s Flask library along with App Engine and Google Cloud Storage. The contributors have extensive knowledge of BigQuery for large and small data storage, manipulation, and analysis purposes and integration into other Google services such as Google Analytics, Google Ads, and Google’s DoubleClick for Publishers.

Amazon Web Services (or AWS) and Google Cloud Platform are seen as direct competitors and offer many of the same services to one another. However, AWS is not extensively covered in the topics on this website.