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Google Cloud Training
"すべてのデータ パイプラインには、データレイクとデータ ウェアハウスという 2 つの主要コンポーネントがあります。このコースでは、各ストレージ タイプのユースケースを紹介し、Google Cloud で利用可能なデータレイクとデータ ウェアハウスのソリューションを技術的に詳しく説明します。また、データ エンジニアの役割や、効果的なデータ パイプラインが事業運営にもたらすメリットについて確認し、クラウド環境でデータ エンジニアリングを行うべき理由を説明します。
これは「Data Engineering on Google Cloud」シリーズの最初のコースです。このコースを修了したら、「Building Batch Data Pipelines on Google Cloud」コースに登録してください。"
Register for this course and see more details by visiting:
OpenCourser.com/course/mb09v7/modernizing
What's inside
Syllabus
はじめに
このモジュールでは「Data Engineering on Google Cloud」コースシリーズと、この「Modernizing Data Lakes and Data Warehouses with Google Cloud」コースについて紹介します。
データ エンジニアリングの概要
Read more
Syllabus
はじめに
このモジュールでは「Data Engineering on Google Cloud」コースシリーズと、この「Modernizing Data Lakes and Data Warehouses with Google Cloud」コースについて紹介します。
データ エンジニアリングの概要
Read more
このモジュールではデータ エンジニアの役割を説明し、クラウドでデータ エンジニアリングを行うべき理由について理解を促します。
データレイクの構築
このモジュールではデータレイクの概要に加え、Google Cloud で Cloud Storage をデータレイクとして使用する方法について説明します。
データ ウェアハウスの構築
このモジュールでは、Google Cloud のデータ ウェアハウジング オプションである BigQuery について説明します。
まとめ
主な学習ポイントのまとめ
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
業界でスタンダードとなったデータレイクを利用できます。
クラウド環境でデータエンジニアリングの第一歩を踏み出せます。
データレイクとデータウェアハウスの基本を学習できます。
Google Cloudのプラットフォームを活用したデータ管理を学べます。
Save this course
Save Modernizing Data Lakes and Data Warehouses with GCP 日本語版 to your list so you can find it easily later:
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Reviews summary
Decent introduction to gcp data engineering
This course provides a basic overview of data lakes and data warehouses in GCP. It covers the basics of data engineering and the role of data engineers. The course also touches on the benefits of using cloud-based data engineering solutions. Overall, this course is a good starting point for learners who are new to data engineering on GCP.
Provides a good overview of data lakes and data warehouses in GCP.
"Good."
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 GCP 日本語版 with these
activities:
Review the basics of data engineering
Show steps
Brush up on the fundamental concepts and vocabulary of data engineering to ensure a strong foundation for this course.
Browse courses on
Data Engineering
Show steps
-
Review online tutorials and articles on data engineering concepts.
-
Complete a practice quiz or assessment to test your understanding.
Attend a data engineering meetup or conference
Show steps
Connect with other data engineers, learn about industry trends, and discover new tools and technologies.
Browse courses on
Data Engineering
Show steps
-
Find a local data engineering meetup or conference.
-
Register for the event and attend.
-
Network with other attendees and speakers.
Join a study group with other students taking the course
Show steps
Enhance your learning experience by collaborating with peers, discussing course material, and working on assignments together.
Browse courses on
Collaboration
Show steps
-
Reach out to other students in your class and propose forming a study group.
-
Meet regularly to discuss the course material, complete assignments, and prepare for exams.
-
Share resources, notes, and insights with your group members.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow a tutorial on building a data lake on Cloud Storage
Show steps
Gain hands-on experience in setting up a data lake on Google Cloud Platform, which is a key component of data engineering pipelines.
Browse courses on
Data Lake
Show steps
-
Find a reputable tutorial on building a data lake on Cloud Storage.
-
Follow the tutorial step-by-step, creating your own data lake in the process.
-
Test your data lake by uploading and querying data.
Create a blog post or article on a data engineering topic
Show steps
Solidify your understanding of data engineering by sharing your knowledge with others.
Browse courses on
Data Engineering
Show steps
-
Choose a specific data engineering topic that you are knowledgeable about.
-
Research and gather information on the topic.
-
Write a well-structured blog post or article, explaining the topic in a clear and engaging manner.
-
Publish your blog post or article on a platform where it can reach a relevant audience.
Develop a data pipeline for a simple use case
Show steps
Apply your knowledge of data engineering by designing and implementing a data pipeline that addresses a specific use case.
Browse courses on
Data Pipeline
Show steps
-
Identify a simple use case for a data pipeline.
-
Design the data pipeline architecture, including data sources, transformations, and destination.
-
Implement the data pipeline using Google Cloud Platform services.
-
Test and evaluate the performance of the data pipeline.
Contribute to an open-source data engineering project
Show steps
Deepen your understanding of data engineering by contributing to a real-world project and collaborating with other developers.
Browse courses on
Open Source
Show steps
-
Find an open-source data engineering project that aligns with your interests.
-
Identify an area where you can make a contribution.
-
Submit a pull request with your proposed changes.
-
Collaborate with the project maintainers to refine and merge your contribution.
Build a data pipeline to address a personal or professional problem
Show steps
Apply your skills to solve a real-world problem, solidifying your understanding of data engineering and its practical applications.
Browse courses on
Data Pipeline
Show steps
-
Identify a personal or professional problem that can be solved using a data pipeline.
-
Design and implement a data pipeline using Google Cloud Platform services.
-
Deploy the data pipeline and monitor its performance.
-
Evaluate the results and make improvements as needed.
Review the basics of data engineering
Show steps
Brush up on the fundamental concepts and vocabulary of data engineering to ensure a strong foundation for this course.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Review online tutorials and articles on data engineering concepts.
- Complete a practice quiz or assessment to test your understanding.
Attend a data engineering meetup or conference
Show steps
Connect with other data engineers, learn about industry trends, and discover new tools and technologies.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Find a local data engineering meetup or conference.
- Register for the event and attend.
- Network with other attendees and speakers.
Join a study group with other students taking the course
Show steps
Enhance your learning experience by collaborating with peers, discussing course material, and working on assignments together.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Reach out to other students in your class and propose forming a study group.
- Meet regularly to discuss the course material, complete assignments, and prepare for exams.
- Share resources, notes, and insights with your group members.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow a tutorial on building a data lake on Cloud Storage
Show steps
Gain hands-on experience in setting up a data lake on Google Cloud Platform, which is a key component of data engineering pipelines.
Browse courses on
Data Lake
Show steps
Show steps
Show steps
- Find a reputable tutorial on building a data lake on Cloud Storage.
- Follow the tutorial step-by-step, creating your own data lake in the process.
- Test your data lake by uploading and querying data.
Create a blog post or article on a data engineering topic
Show steps
Solidify your understanding of data engineering by sharing your knowledge with others.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Choose a specific data engineering topic that you are knowledgeable about.
- Research and gather information on the topic.
- Write a well-structured blog post or article, explaining the topic in a clear and engaging manner.
- Publish your blog post or article on a platform where it can reach a relevant audience.
Develop a data pipeline for a simple use case
Show steps
Apply your knowledge of data engineering by designing and implementing a data pipeline that addresses a specific use case.
Browse courses on
Data Pipeline
Show steps
Show steps
Show steps
- Identify a simple use case for a data pipeline.
- Design the data pipeline architecture, including data sources, transformations, and destination.
- Implement the data pipeline using Google Cloud Platform services.
- Test and evaluate the performance of the data pipeline.
Contribute to an open-source data engineering project
Show steps
Deepen your understanding of data engineering by contributing to a real-world project and collaborating with other developers.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find an open-source data engineering project that aligns with your interests.
- Identify an area where you can make a contribution.
- Submit a pull request with your proposed changes.
- Collaborate with the project maintainers to refine and merge your contribution.
Build a data pipeline to address a personal or professional problem
Show steps
Apply your skills to solve a real-world problem, solidifying your understanding of data engineering and its practical applications.
Browse courses on
Data Pipeline
Show steps
Show steps
Show steps
- Identify a personal or professional problem that can be solved using a data pipeline.
- Design and implement a data pipeline using Google Cloud Platform services.
- Deploy the data pipeline and monitor its performance.
- Evaluate the results and make improvements as needed.
Career center
Learners who complete Modernizing Data Lakes and Data Warehouses with GCP 日本語版 will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers oversee big data pipelines and ensure data integrity and accessibility. This course provides a solid foundation in data lakes, data warehouses, and cloud-based data engineering, all of which are essential aspects of modern data engineering. By understanding the concepts and technologies covered in this course, you can gain an advantage in the competitive field of data engineering.
Data Analyst
Data Analyst
Data Analysts use data to derive insights and solve business problems. This course helps build a foundation in modern data storage and processing technologies, which are essential for data analysis. By completing this course, you will gain a deeper understanding of how to use data lakes and data warehouses to support data analysis initiatives.
Data Scientist
Data Scientist
Data Scientists leverage data to develop predictive models and statistical algorithms. This course provides a comprehensive introduction to data lakes and data warehouses, which are critical for storing and managing the vast amounts of data used in data science projects. The course also covers cloud-based data engineering, which is becoming increasingly important in the field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and implement machine learning models. This course provides a solid foundation in data lakes and data warehouses, which are essential for managing the large datasets used in machine learning. By understanding the principles and technologies covered in this course, you can enhance your skills as a Machine Learning Engineer.
Data Architect
Data Architect
Data Architects design and manage data systems. This course provides a comprehensive overview of data lakes and data warehouses, which are key components of modern data architectures. By completing this course, you will gain a deeper understanding of how to design and implement effective data architectures that meet the needs of your organization.
Cloud Engineer
Cloud Engineer
Cloud Engineers design and manage cloud-based infrastructure. This course provides a solid introduction to data lakes and data warehouses in the cloud, which are becoming increasingly important for modern cloud architectures. By understanding the concepts and technologies covered in this course, you can enhance your skills as a Cloud Engineer.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course provides a comprehensive overview of data lakes and data warehouses, which are becoming increasingly popular alternatives to traditional databases. By completing this course, you will gain a deeper understanding of how to manage and maintain these modern data storage systems.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and implement data warehouses. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on data warehouse architecture. By completing this course, you will gain a deeper understanding of how to design and implement effective data warehouses that meet the needs of your organization.
Data Lake Architect
Data Lake Architect
Data Lake Architects design and implement data lakes. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on data lake architecture. By completing this course, you will gain a deeper understanding of how to design and implement effective data lakes that meet the needs of your organization.
Data Integration Architect
Data Integration Architect
Data Integration Architects design and implement data integration solutions. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on data integration. By completing this course, you will gain a deeper understanding of how to design and implement effective data integration solutions that meet the needs of your organization.
Information Architect
Information Architect
Information Architects design and implement information systems. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on information architecture. By completing this course, you will gain a deeper understanding of how to design and implement effective information systems that meet the needs of your organization.
Data Governance Specialist
Data Governance Specialist
Data Governance Specialists ensure the quality and integrity of data. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on data governance. By completing this course, you will gain a deeper understanding of how to design and implement effective data governance policies and practices.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to derive insights and solve business problems. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on business intelligence. By completing this course, you will gain a deeper understanding of how to use data lakes and data warehouses to support business intelligence initiatives.
Data Management Consultant
Data Management Consultant
Data Management Consultants help organizations manage their data. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on data management. By completing this course, you will gain a deeper understanding of how to help organizations manage their data effectively.
Data Privacy Specialist
Data Privacy Specialist
Data Privacy Specialists ensure that data is used in a compliant and ethical manner. This course provides a comprehensive overview of data lakes and data warehouses, with a focus on data privacy. By completing this course, you will gain a deeper understanding of how to design and implement effective data privacy policies and practices.
For more career information including salaries, visit:
OpenCourser.com/course/mb09v7/modernizing
Reading list
We've selected nine 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 GCP 日本語版.
Save
データメッシュアーキテクチャの詳細を調査し、ビジネスユーザーがデータをより効果的に活用できる方法を理解するに役立ちます。
ビッグデータと機械学習の交差を調査し、大規模データセットからのインサイトの抽出に役立つ手法とテクノロジーを説明します。
NoSQLデータベースの概念と種類を解説し、さまざまなユースケースやビジネス要件に基づいて適切なソリューションを選択するのに役立ちます。
Apache Sparkの包括的な概要を提供し、大規模データ処理、ストリーミング、機械学習のための技術的詳細と実践的なガイダンスを記載しています。
ビッグデータの概念、テクノロジー、およびアプリケーションを調査し、企業におけるビッグデータ活用に関する包括的な概要を提供します。
Hadoopエコシステムの包括的な概要を提供し、大規模データ処理のための技術的詳細と実践的なガイダンスを記載しています。
データウェアハウジング用のETLプロセスの技術的詳細を調査し、さまざまなデータソースからデータを抽出し、クリーニングし、変換し、ロードするための実用的なガイダンスを提供します。
データ統合の原理と手法を調査し、さまざまなデータソースからのデータを統合して価値あるインサイトを作成する方法を説明します。
データウェアハウジングのベストプラクティスとパターンを網羅し、効果的なデータウェアハウスを設計、構築、管理するためのガイダンスを提供します。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mb09v7/modernizing
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Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
日本語
Transcript
English
This course belongs to a
collection
called
Data Engineering, Big Data and ML on Google Cloud 日本語版. It's comprised of five courses:
- Building Resilient Streaming Analytics Systems on GCP 日本語版
- Smart Analytics, Machine Learning, and AI on GCP 日本語版
- Google Cloud Big Data and Machine Learning Fundamentals 日本語版
- Modernizing Data Lakes and Data Warehouses with GCP 日本語版 (viewing)
- Building Batch Data Pipelines on GCP 日本語版
Good to know
業界でスタンダードとなったデータレイクを利用できます。
クラウド環境でデータエンジニアリングの第一歩を踏み出せます。
データレイクとデータウェアハウスの基本を学習できます。
Google Cloudのプラットフォームを活用したデータ管理を学べます。
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