Overview
Key Features
The two key components of any data pipeline are data lakes and warehouses. 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.
This Modernizing Data Lakes and Data Warehouses with Google Cloud course offered by Coursera in partnership with Google Cloud is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
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Visit programme websiteProgramme Structure
Courses include:
Data Engineering
Building a Data Lake
Building a data warehouse
Summary
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Computer Sciences Data Science & Big Data Machine Learning View 583 other Short Courses in Data Science & Big Data in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate Level
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.