Automating your BigQuery Data Pipeline with Cloud Dataprep

Google Cloud, located in Toronto, North America, offers you a unique blend of academic and professional opportunities. As a institution founded in 2008, it provides a fresh perspective on education. You will find advantages in its strong focus on computing, data storage, and machine learning, making it an ideal choice for students interested in these fields. Its client base spans various industries, including financial services, healthcare, retail, and education, providing you with a broad range of potential collaborations and career paths.

Specifically, Google Cloud focuses on services like computing, data analytics, and machine learning, with tools such as Google Cloud Platform (GCP) and Google Workspace. You can choose from 723 programs, which cover a broad spectrum of subjects. Key languages and technologies are taught, preparing you for a career in these in-demand fields. For instance, you can develop skills in Gmail, Docs, Drive, and Calendar, making you proficient in Google's suite of productivity tools.

In Toronto, you will find a unique city benefit - a diverse and thriving metropolis with many opportunities for internships, collaborations, and networking. You can take advantage of the city's active startup scene, with many companies using Google Cloud services. On campus, you can engage with a community of 30,000 students, including many international students, creating a dynamic and global learning environment. Opportunities for you include accessing modern labs, and participating in active student clubs, making your time at Google Cloud a rich and rewarding experience.

This Non-degree program, offered by Google Cloud in English, teaches students how to automate their BigQuery data pipeline with Cloud Dataprep. It takes place online over several weeks and is self-paced.

The curriculum covers complicated data structures in BigQuery and how to use Dataprep to work with them. Students develop skills in data pipeline automation and data preparation.

Graduates can work as Data Engineers, Cloud Architects, Data Analysts, Business Intelligence Developers, or Data Scientists, helping companies automate their data pipelines and work with complex data structures.