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Modernizing Data Lakes and Data Warehouses with Google Cloud

Google Cloud Training

4.7

Based on 2,826 ratings

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Google Cloud Training

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.

This 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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What's inside

Syllabus

Introduction

This module introduces the Data Engineering on Google Cloud source series and this Modernizing Data Lakes and Data Warehouses with Google Cloud course.

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Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Builds a solid foundational understanding of data engineering's role in the cloud

Teaches learners about the practical use of Google Cloud's data lake and warehouse solutions

Examines a variety of use cases for implementing data lakes and warehouses within a data pipeline

Is part of a broader series on data engineering on Google Cloud, offering a structured learning path

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Reviews summary

Introduction to gcp data lakes and warehouses

According to learners, this course provides a strong introduction to the concepts of data lakes and data warehouses, specifically focusing on their implementation using Google Cloud services like Cloud Storage and BigQuery. It serves as an excellent foundational course for the Data Engineering on Google Cloud series. Reviewers largely found the explanations of core concepts to be clear and helpful. However, some noted that while it offers a solid overview, the course could benefit from more technical depth for those with prior experience.

Serves as a strong foundation for the series.

"Great way to start the Data Engineering on Google Cloud specialization."

"Sets the stage well for subsequent courses."

"I feel ready to move on to the next course after completing this one."

Clearly explains data lake/warehouse differences.

"The distinction between data lakes and warehouses was very clear after this module."

"Understanding the concepts was made easy."

"Helped me solidify my understanding of these fundamental data concepts."

Good introduction to Cloud Storage and BigQuery.

"This course gave me a great first look at how Cloud Storage and BigQuery fit together for data."

"I learned the basics of using Google Cloud for data storage and warehousing."

"Provides a clear overview of the main GCP data tools covered."

Content is introductory, lacks advanced detail.

"Found it a bit too basic, expected more technical depth on BigQuery."

"Good overview, but doesn't dive deep enough for experienced users."

"Could benefit from more advanced topics or use case examples."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Modernizing Data Lakes and Data Warehouses with Google Cloud with these activities:

Review Python Programming

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Refreshes Python programming skills for effective data engineering.

Browse courses on Python

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Review the basics of Python syntax and data structures.
Practice writing simple Python programs.

Review of Basics of Modern Data Engineering

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Reinforce your understanding of the fundamental concepts related to data engineering, data lakes, and data warehouses to build a stronger foundation.

Browse courses on Data Pipeline

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Review data warehousing concepts.
Re-familiarize yourself with data lake concepts.
Explore the basics of cloud computing.

Explore Data Engineering Concepts

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Provides a foundation for understanding data engineering concepts.

Browse courses on Data Engineering

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Review the course syllabus and learning objectives.
Read the assigned textbook chapters.
Complete the practice exercises provided in the course materials.

13 other activities

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Guided Tutorial on Data Engineering Tools

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Become familiar with essential data engineering tools used in the course

Browse courses on Google Cloud

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Follow tutorials on using Google Cloud data engineering tools
Complete hands-on exercises to apply what you've learned

Build a Data Pipeline with Cloud Dataflow

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Provides hands-on experience in building data pipelines using Cloud Dataflow.

Browse courses on Data Pipelines

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Find a tutorial on building data pipelines with Cloud Dataflow.
Follow the tutorial to build a data pipeline.
Test the data pipeline and make necessary adjustments.

Build a Data Lake using Cloud Storage

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Build a foundation in using Cloud Storage for data lake applications

Browse courses on Data Lakes

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Create a Cloud Storage bucket
Upload sample data to the bucket
Develop a script to query data from the bucket

Practice Data Engineering Queries

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Improve proficiency in writing efficient data engineering queries

Browse courses on SQL

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Solve practice problems using SQL
Analyze query performance and optimize queries

Join a Data Engineering Study Group

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Engage with peers to discuss course concepts, share knowledge, and work through challenges together.

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Find a study partner or group.
Establish a regular meeting schedule.
Discuss course materials, ask questions, and solve problems.

Design a Data Warehouse using BigQuery

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Gain hands-on experience designing a data warehouse using BigQuery

Browse courses on Data Warehouse

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Create a BigQuery dataset
Import sample data into the dataset
Develop SQL queries to analyze the data

Guided Tutorials on Google Cloud Storage

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Deepen your knowledge of Google Cloud Storage, a key component for building data lakes on Google Cloud.

Browse courses on Google Cloud Storage

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Explore tutorials on creating and managing buckets.
Practice uploading, downloading, and managing objects.
Learn about security and access control for data lakes.

BigQuery Practice Exercises

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Enhance your proficiency in BigQuery by completing a set of practice exercises.

Browse courses on BigQuery

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Execute SQL queries to extract and analyze data.
Create tables, views, and datasets.
Explore data visualization and reporting features.

Implement a Data Warehouse Solution

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Gains experience in implementing data warehouse solutions in the cloud.

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Gather requirements for the data warehouse.
Design the data warehouse schema.
Load data into the data warehouse.
Create queries to access and analyze data from the data warehouse.

Develop a Data Pipeline for a Real-World Dataset

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Apply your knowledge to a practical project by building a data pipeline that addresses a real-world problem.

Browse courses on Data Pipelines

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Identify a dataset and define the problem statement.
Design the data pipeline architecture.
Implement data ingestion, processing, and analysis.
Deploy the pipeline and monitor its performance.

Design a Data Lake Architecture

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Demonstrate your understanding of data lake concepts by designing an architecture for a specific use case.

Browse courses on Data Engineering

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Identify the requirements and goals of the data lake.
Choose appropriate data sources and storage formats.
Design the data ingestion and processing pipelines.
Implement security and governance measures.

Develop a Data Engineering Project

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Provides an opportunity to apply data engineering skills to a real-world project.

Browse courses on Cloud Data Engineering

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Identify a business problem that can be solved using data engineering.
Design a data engineering solution to solve the problem.
Implement the data engineering solution.
Evaluate the results of the data engineering solution.

Contribute to the Google Cloud Data Engineering GitHub Repository

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Gain practical experience and contribute to the data engineering community by working on real-world projects.

Browse courses on Data Engineering

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Identify an open issue or feature request.
Propose a solution or implementation.
Submit a pull request to the repository.
Collaborate with other contributors to improve the project.

Career center

Learners who complete Modernizing Data Lakes and Data Warehouses with Google Cloud will develop knowledge and skills that may be useful to these careers:

Cloud Data Engineer

Cloud Data Engineers design, build, and manage data pipelines and data infrastructure in the cloud. They work with cloud platforms such as AWS, Azure, and Google Cloud, leveraging cloud-native services and tools to build scalable, reliable, and cost-effective data solutions. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Cloud Data Engineers with an in-depth understanding of Google Cloud's data storage and management offerings. Through hands-on labs and real-world examples, learners gain practical experience in designing and implementing data pipelines using Cloud Storage, BigQuery, and other Google Cloud services.

See salaries and explore the career path for Cloud Data Engineer

Data Engineer

Data Engineers use programming and engineering practices to design and build scalable, reliable, and efficient data systems. They work with various data sources such as databases, data lakes, and data warehouses, ensuring data integrity, security, and accessibility. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides a solid foundation for aspiring Data Engineers by introducing them to the concepts of data lakes and warehouses and their implementation on Google Cloud Platform. With hands-on labs and real-world examples, learners gain practical experience in building and managing data pipelines, which is essential for success in this role.

See salaries and explore the career path for Data Engineer

Data Warehouse Engineer

Data Warehouse Engineers specialize in designing, building, and maintaining data warehouses. They work with data architects and data analysts to ensure the data warehouse meets the organization's data storage and processing requirements. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Data Warehouse Engineers with in-depth knowledge of BigQuery, a leading cloud data warehouse solution. Through hands-on labs and real-world examples, learners gain practical experience in designing and managing data warehouses, essential for success in this role.

See salaries and explore the career path for Data Warehouse Engineer

Data Architect

Data Architects design and manage data systems and pipelines, ensuring they meet the organization's business requirements. They work closely with stakeholders to understand data needs, design data models, and implement data governance policies. This course provides Data Architects with an understanding of modern data lakes and data warehouses on Google Cloud. Learning about the capabilities and best practices of Cloud Storage and BigQuery empowers them to make informed decisions when designing and implementing data solutions that align with the latest cloud technologies.

See salaries and explore the career path for Data Architect

Data Scientist

Data Scientists leverage data to extract insights and solve business problems. They use statistical modeling, machine learning, and other analytical techniques to uncover patterns, trends, and anomalies in data. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Data Scientists with a foundational understanding of data storage and management technologies. By learning about the capabilities of Cloud Storage and BigQuery, they can effectively access and analyze large datasets to support their data science projects.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts analyze data to extract insights and identify trends. They use statistical techniques, data visualization tools, and machine learning algorithms to uncover patterns and relationships in data. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Data Analysts with an understanding of data storage and management technologies. Learning about the capabilities of Cloud Storage and BigQuery enables them to access and analyze large datasets efficiently, supporting their role in providing valuable insights to the business.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

Business Intelligence Analysts gather, analyze, and interpret data to provide insights that inform business decisions. They work with stakeholders across the organization to identify data needs, develop reports and visualizations, and communicate findings. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Business Intelligence Analysts with an understanding of the latest data storage and management technologies. Learning about the capabilities of Cloud Storage and BigQuery enables them to access and analyze data efficiently, supporting their role in providing valuable insights to the business.

See salaries and explore the career path for Business Intelligence Analyst

Database Administrator

Database Administrators ensure the reliability, performance, and security of databases. They work with database systems such as MySQL, Oracle, and PostgreSQL, managing user access, optimizing performance, and implementing backup and recovery strategies. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Database Administrators with an understanding of cloud-based data storage and management solutions. Learning about the capabilities of Cloud Storage and BigQuery enables them to explore alternative data storage options and consider cloud migration strategies.

See salaries and explore the career path for Database Administrator

Cloud Engineer

Cloud Engineers design, build, and manage cloud infrastructure and services. They work with cloud platforms such as AWS, Azure, and Google Cloud, ensuring the availability, scalability, and security of cloud-based applications and services. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Cloud Engineers with an understanding of data storage and management in the cloud. Learning about the capabilities of Cloud Storage and BigQuery enables them to design and implement data solutions that leverage the benefits of cloud computing.

See salaries and explore the career path for Cloud Engineer

Information Architect

Information Architects design and manage information systems and structures. They work with stakeholders to understand information needs, develop taxonomies and metadata, and ensure the accessibility and usability of information. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Information Architects with an understanding of cloud-based data storage and management solutions. Learning about the capabilities of Cloud Storage and BigQuery enables them to explore alternative data storage options and consider cloud migration strategies for their organizations.

See salaries and explore the career path for Information Architect

IT Architect

IT Architects design, build, and maintain IT infrastructure and systems. They work with various technologies, including hardware, software, networks, and cloud platforms, to ensure the reliability, performance, and security of IT systems. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides IT Architects with an understanding of cloud-based data storage and management solutions. Learning about the capabilities of Cloud Storage and BigQuery enables them to explore alternative data storage options and consider cloud migration strategies for their organizations.

See salaries and explore the career path for IT Architect

Privacy Engineer

Privacy Engineers design and implement technical solutions to protect personal data and comply with privacy regulations. They work with legal, compliance, and IT teams to assess privacy risks, develop data protection strategies, and implement privacy-enhancing technologies. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Privacy Engineers with an understanding of cloud-based data storage and management solutions. Learning about the capabilities of Cloud Storage and BigQuery enables them to explore alternative data storage options and consider cloud migration strategies in the context of data privacy.

See salaries and explore the career path for Privacy Engineer

Data Security Analyst

Data Security Analysts protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. They work with IT security teams to implement data security measures, monitor data access, and respond to security incidents. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Data Security Analysts with an understanding of cloud-based data storage and management solutions. Learning about the capabilities of Cloud Storage and BigQuery enables them to explore alternative data storage options and consider cloud migration strategies in the context of data security.

See salaries and explore the career path for Data Security Analyst

Data Governance Specialist

Data Governance Specialists develop and implement policies and procedures to ensure the quality, consistency, and security of data. They work with stakeholders across the organization to define data governance standards, monitor data usage, and enforce data compliance. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Data Governance Specialists with an understanding of cloud-based data storage and management solutions. Learning about the capabilities of Cloud Storage and BigQuery enables them to explore alternative data storage options and consider cloud migration strategies in the context of data governance.

See salaries and explore the career path for Data Governance Specialist

Software Engineer

Software Engineers design, develop, and maintain software applications. They work with programming languages, software development tools, and cloud platforms to build and deploy software solutions. This course on Modernizing Data Lakes and Data Warehouses with Google Cloud provides Software Engineers with an understanding of data storage and management technologies. Learning about the capabilities of Cloud Storage and BigQuery enables them to integrate data-driven features into their software applications, enhancing their functionality and value.

See salaries and explore the career path for Software Engineer

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Modernizing Data Lakes and Data Warehouses with Google Cloud.

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Cover image

The Azure Data Lakehouse Toolkit

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Provides comprehensive coverage of Google Cloud's data lake and warehouse solutions and valuable resource for those who want to dive deeper into the technical details of these technologies.

The Azure Data Lakehouse Toolkit: Building and...

The Azure Data Lakehouse Toolkit: Building and...

Cover image

Cover image

Mastering the SAP Business Information Warehouse

Save

Classic in the field of data warehousing. It provides a comprehensive overview of data warehousing concepts, technologies, and applications. It valuable resource for those looking to learn more about data warehousing.

Mastering the SAP Business Information Warehouse

Mastering the SAP Business Information Warehouse

Cover image

Cover image

Hadoop Operations

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Provides a comprehensive overview of Hadoop operations, including performance tuning and security.

Hadoop Operations: A Guide for Developers and...

Hadoop Operations by Eric Sammer (2012-10-19)

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The Kimball Group Reader

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This classic book provides a foundational understanding of data warehousing concepts and principles, which are essential for building and managing effective data warehouses.

The Kimball Group Reader

The Kimball Group Reader

Cover image

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Fundamentals of Machine Learning for Predictive...

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Provides a broader perspective on data science and big data analytics, which is helpful for understanding the role of data lakes and warehouses in the larger context of data-driven decision-making.

Fundamentals of Machine Learning for Predictive...

Fundamentals of Machine Learning for Predictive...

Cover image

Cover image

The Pluto System After New Horizons

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Provides a gentle introduction to data lakes and good resource for those who are new to the concept.

The Pluto System After New Horizons (The University...

The Pluto System After New Horizons (The University...

Cover image

Cover image

Mastering Data Warehouse Aggregates

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Provides a gentle introduction to data warehouses and good resource for those who are new to the concept.

Mastering Data Warehouse Aggregates: Solutions for...

Mastering Data Warehouse Aggregates: Solutions for...

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Rating

4.7

Effort

Approx. 8 hours

Level

Intermediate

Via

Coursera

Institution

Google Cloud

Instructor

Google Cloud Training

Language

English

Modernizing Data Lakes and Data Warehouses with Google Cloud belongs to the following collections:

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Builds a solid foundational understanding of data engineering's role in the cloud

Teaches learners about the practical use of Google Cloud's data lake and warehouse solutions

Examines a variety of use cases for implementing data lakes and warehouses within a data pipeline

Is part of a broader series on data engineering on Google Cloud, offering a structured learning path

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