What you will learn
Differentiate between data lakes and data warehouses.
Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.
Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.
Examine why data engineering should be done in a cloud environment.
Program Overview
Introduction
⏳ 3 minutes
Introduces the Data Engineering on Google Cloud series and this specific course.
Introduction to Data Engineering
⏳ 1 hour
Discusses the role of data engineering and the rationale for performing data engineering in the cloud.
Building a Data Lake
⏳ 1 hour
Describes what a data lake is and how to use Cloud Storage as your data lake on Google Cloud
Building a Data Warehouse
⏳ 5 hours
Explores BigQuery as a data warehousing solution on Google Cloud.
Summary
⏳ 2 minutes
Summarizes the key learning points from the course.
Get certificate
Job Outlook
- Proficiency in data lakes and data warehouses is valuable for roles such as Data Engineer, Data Analyst, and Cloud Architect.
- Skills acquired in this course are applicable across various industries, including finance, healthcare, and technology.
- Completing this course can enhance your qualifications for positions that require expertise in cloud-based data storage and processing solutions.
Explore More Learning Paths
Enhance your data engineering and cloud analytics skills with these curated courses designed to help you modernize data lakes and warehouses, optimize storage, and improve data-driven decision-making.
Related Courses
IBM Data Warehouse Engineer Professional Certificate Course – Learn to design, build, and manage modern data warehouses for enterprise-scale analytics.
Data Engineering Foundations Specialization Course – Build a strong foundation in data engineering concepts, including pipelines, storage, and cloud integration.
IBM Data Architecture Professional Certificate Course – Explore advanced data architecture techniques to optimize data storage, access, and analytics.
Related Reading
What Is Data Management? – Gain insights into effective data management strategies that complement modern data lakes and warehouses.
Specification: Modernizing Data Lakes and Data Warehouses with Google Cloud
|
FAQs
- Covers cloud-based data storage and management
- Explains data lake and warehouse modernization strategies
- Uses Google Cloud tools like BigQuery and Dataproc
- Focuses on scalability, performance, and cost efficiency
- Data engineers and analysts
- IT professionals managing legacy systems
- Cloud architects working with enterprise data
- Anyone aiming to specialize in Google Cloud data services
- Understanding differences between on-premises and cloud systems
- Migrating and managing data on Google Cloud
- Using BigQuery for analytics at scale
- Optimizing storage, processing, and querying
- Knowledge of SQL is helpful
- Basic understanding of data lakes and warehouses is useful
- No deep programming expertise required
- Step-by-step guidance provided
- Opens opportunities in cloud data engineering
- Enhances qualifications for Google Cloud-related roles
- Builds expertise valued in analytics and big data fields
- Strengthens your resume with cloud modernization skills
