The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
About this Course
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
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TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GOOGLE CLOUD
A better understanding of BigQuery starts here. A vital resource for consultants, data analysts, and product managers, and an important reference source for engineers and data scientists.
The course offers a nice description of what modern DWH means, which are the differences between classic DWH and cloud DWH. You have the chance to work with the new cloud concept on GCP.
Very valuable information about data lakes, data warehouses, using Arrays and Structs to store data in BigQuery. Loved the course.
In depth course explaining how to build scalable & state of the art data lakes & data warehouse on GCS, CloudSQL, Bigquery. Ways to optimize bigquery & improve the schema
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