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Google Cloud Training
Traiter des flux de données est une pratique de plus en plus populaire, car ceux-ci permettent aux entreprises d'obtenir des métriques sur leurs activités commerciales en temps réel. Ce cours explique comment créer des pipelines de flux de données sur Google Cloud et présente Pub/Sub, une solution qui permet de gérer des données de flux entrants. Par ailleurs, vous verrez comment appliquer des agrégations et des transformations à des flux de données à l'aide de Dataflow, mais aussi comment stocker des enregistrements traités dans BigQuery ou Cloud Bigtable pour qu'ils puissent être analysés. Les participants mettront en pratique les connaissances qu'ils auront acquises en créant des composants de pipelines de flux de données sur Google Cloud à l'aide de Qwiklabs.
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What's inside
Syllabus
Présentation
Ce module vous présente le cours et son déroulement.
Présentation du traitement de flux de données
Ce module aborde les problèmes liés au traitement de flux de données.
Read more
Syllabus
Présentation
Ce module vous présente le cours et son déroulement.
Présentation du traitement de flux de données
Ce module aborde les problèmes liés au traitement de flux de données.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Exploite les fonctionnalités de BigQuery avancées pour répondre aux besoins de flux de données complexes de votre entreprise
Intègre les composants de Google Cloud Platform pour traiter et analyser les flux de données
Développe des compétences pratiques sur les applications du monde réel à l'aide de Qwiklabs
Développe une solide compréhension de Pub/Sub pour gérer les flux de données entrants
Renforce une base existante sur Dataflow, en particulier sur ses capacités de traitement de flux de données
Conçu pour les développeurs de données, les analystes de données et les autres professionnels travaillant avec des flux de données
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Reviews summary
Fondamentaux de l'analyse de flux sur gcp
Selon les apprenants, ce cours est une excellente introduction et un point de départ solide pour quiconque souhaite maîtriser les systèmes d'analyse de flux sur Google Cloud Platform. Beaucoup soulignent la clarté des explications sur des services clés comme Pub/Sub, Dataflow, BigQuery et Cloud Bigtable. Les labs Qwiklabs sont universellement appréciés pour leur utilité pratique, permettant une application directe des connaissances. Cependant, certains estiment que le cours, bien que pertinent pour les débutants, manque de profondeur sur les sujets avancés et les cas d'usage en production. Il est idéal pour ceux qui débutent ou cherchent à solidifier leurs bases, mais les experts pourraient trouver certaines parties trop basiques.
Parfait pour ceux qui découvrent les technologies de streaming.
"Ce cours est fantastique pour comprendre les bases des systèmes d'analyse de flux sur GCP."
"Un bon cours pour démarrer avec le streaming sur GCP... C'est une excellente introduction..."
"C'est un excellent point de départ pour les débutants sur ces technologies."
Fournit des bases solides sur les services GCP de streaming.
"Ce cours est fantastique pour comprendre les bases des systèmes d'analyse de flux sur GCP. Les explications sur Pub/Sub et Dataflow sont très claires..."
"J'ai vraiment consolidé ma compréhension de Pub/Sub et de l'architecture de flux de données résiliente."
"J'ai trouvé ce cours extrêmement utile. Les explications sont claires et concises. Je recommande vivement pour quiconque veut comprendre les bases..."
Les exercices pratiques sont très efficaces pour l'apprentissage.
"Les labs Qwiklabs sont incroyablement utiles pour la pratique. J'ai vraiment apprécié la section sur BigQuery et Bigtable pour l'analyse des données."
"Absolument génial ! Les labs Qwiklabs m'ont permis de mettre en pratique tout ce que j'apprenais. Le rythme est parfait."
"J'ai trouvé ce cours extrêmement utile. Les explications sont claires et concises. Les exercices pratiques via Qwiklabs sont un vrai plus et aident à la rétention des connaissances."
Peut être trop basique pour les utilisateurs expérimentés.
"J'aurais aimé plus de cas pratiques avancés ou des exemples concrets de déploiement en production."
"Pour quelqu'un qui a déjà une certaine expérience avec GCP, une grande partie du contenu peut sembler redondante ou trop basique."
"Le contenu est très généraliste et ne va pas assez loin pour des usages avancés en entreprise. Cela dit, c'est un excellent point de départ."
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 Building Resilient Streaming Analytics Systems on GCP en Français with these
activities:
Review core concepts of data processing
Show steps
Reviewing data processing fundamentals will ensure a solid base to understand advanced concepts taught in the course.
Browse courses on
Data Processing
Show steps
-
Examine your existing notes or textbooks from previous data processing courses
-
Go over online resources or tutorials to refresh your memory on key concepts
-
Complete practice problems or exercises to test your understanding
Organize or participate in study groups for the course
Show steps
Collaboration with peers through study groups provides opportunities to discuss concepts, clarify doubts, and reinforce your understanding.
Browse courses on
Collaboration
Show steps
-
Connect with classmates or fellow learners to form or join a study group
-
Establish regular meeting times and create a shared agenda
-
Review course materials together, discuss key concepts, and work through practice problems
-
Provide support and encouragement to each other
Explore Google Cloud's Dataflow documentation
Show steps
Hands-on exploration of the Dataflow documentation will familiarize you with its capabilities and enhance your understanding of its role in data processing.
Browse courses on
Dataflow
Show steps
-
Navigate to the official Google Cloud Dataflow documentation
-
Review the introductory sections to gain an overview of Dataflow's purpose and features
-
Explore specific sections related to data ingestion, transformation, and storage to understand how Dataflow processes streaming data
-
Follow along with code examples or tutorials to apply your knowledge in a practical context
Two other activities
Expand to see all activities and additional details
Show all five activities
Develop a data processing solution for a specific business problem
Show steps
Applying data processing to solve a real-world business problem will enhance your critical thinking and problem-solving abilities.
Browse courses on
Data-Driven Decision Making
Show steps
-
Identify a business problem that can be addressed using data processing techniques
-
Gather and analyze data relevant to the problem
-
Design and implement a data processing solution using Google Cloud technologies
-
Interpret the results and draw meaningful insights
-
Present your findings and recommendations to stakeholders
Participate in online data processing hackathons
Show steps
Participation in data processing hackathons will challenge your skills, foster creativity, and expose you to innovative approaches.
Browse courses on
Data Challenges
Show steps
-
Identify and register for relevant data processing hackathons
-
Collaborate with a team or work individually to solve the proposed challenge
-
Develop and submit a solution that meets the hackathon requirements
-
Attend the hackathon event to showcase your work
-
Network with other participants and learn from their experiences
Review core concepts of data processing
Show steps
Reviewing data processing fundamentals will ensure a solid base to understand advanced concepts taught in the course.
Browse courses on
Data Processing
Show steps
Show steps
Show steps
- Examine your existing notes or textbooks from previous data processing courses
- Go over online resources or tutorials to refresh your memory on key concepts
- Complete practice problems or exercises to test your understanding
Organize or participate in study groups for the course
Show steps
Collaboration with peers through study groups provides opportunities to discuss concepts, clarify doubts, and reinforce your understanding.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Connect with classmates or fellow learners to form or join a study group
- Establish regular meeting times and create a shared agenda
- Review course materials together, discuss key concepts, and work through practice problems
- Provide support and encouragement to each other
Explore Google Cloud's Dataflow documentation
Show steps
Hands-on exploration of the Dataflow documentation will familiarize you with its capabilities and enhance your understanding of its role in data processing.
Browse courses on
Dataflow
Show steps
Show steps
Show steps
- Navigate to the official Google Cloud Dataflow documentation
- Review the introductory sections to gain an overview of Dataflow's purpose and features
- Explore specific sections related to data ingestion, transformation, and storage to understand how Dataflow processes streaming data
- Follow along with code examples or tutorials to apply your knowledge in a practical context
Two other activities
Expand to see all activities and additional details
Show all five activities
Develop a data processing solution for a specific business problem
Show steps
Applying data processing to solve a real-world business problem will enhance your critical thinking and problem-solving abilities.
Browse courses on
Data-Driven Decision Making
Show steps
Show steps
Show steps
- Identify a business problem that can be addressed using data processing techniques
- Gather and analyze data relevant to the problem
- Design and implement a data processing solution using Google Cloud technologies
- Interpret the results and draw meaningful insights
- Present your findings and recommendations to stakeholders
Participate in online data processing hackathons
Show steps
Participation in data processing hackathons will challenge your skills, foster creativity, and expose you to innovative approaches.
Browse courses on
Data Challenges
Show steps
Show steps
Show steps
- Identify and register for relevant data processing hackathons
- Collaborate with a team or work individually to solve the proposed challenge
- Develop and submit a solution that meets the hackathon requirements
- Attend the hackathon event to showcase your work
- Network with other participants and learn from their experiences
Career center
Learners who complete Building Resilient Streaming Analytics Systems on GCP en Français will develop knowledge and skills
that may be useful to these careers:
Quality Assurance Analyst
Quality Assurance Analyst
A Quality Assurance Analyst tests and evaluates software products to ensure they meet quality standards. They must have a strong understanding of quality assurance principles and practices. This course may be useful for aspiring Quality Assurance Analysts as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Quality Assurance Analysts test and evaluate software products effectively.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and maintains cloud computing solutions. They must have a deep understanding of cloud platforms and services. This course may be useful for aspiring Cloud Architects as it covers topics like Pub/Sub, Dataflow, BigQuery, and Cloud Bigtable. Understanding these technologies can help Cloud Architects make informed decisions when designing and implementing cloud solutions.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, interprets, and presents data to help organizations make informed decisions. This course may be useful for aspiring Data Analysts as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Data Analysts build and maintain effective data pipelines.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. They must have a strong understanding of software engineering principles and practices. This course may be useful for aspiring Software Engineers as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Software Engineers build reliable and scalable software systems.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods to extract knowledge and insights from data. They must have a strong understanding of statistics, machine learning, and data analysis techniques. This course may be useful for aspiring Data Scientists as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Data Scientists build and maintain effective data pipelines.
Business Analyst
Business Analyst
A Business Analyst identifies and solves business problems by analyzing data and making recommendations. They must have a strong understanding of business processes and data analysis techniques. This course may be useful for aspiring Business Analysts as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Business Analysts build and maintain effective data pipelines.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. They must have a strong understanding of database technologies and principles. This course may be useful for aspiring Database Administrators as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Database Administrators build and maintain reliable and scalable databases.
Systems Analyst
Systems Analyst
A Systems Analyst analyzes and designs computer systems. They must have a strong understanding of systems engineering principles and practices. This course may be useful for aspiring Systems Analysts as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Systems Analysts design and implement reliable and scalable systems.
Information Security Analyst
Information Security Analyst
An Information Security Analyst protects information systems from unauthorized access, use, disclosure, disruption, modification, or destruction. They must have a strong understanding of information security principles and practices. This course may be useful for aspiring Information Security Analysts as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Information Security Analysts build and maintain secure and reliable systems.
Network Administrator
Network Administrator
A Network Administrator manages and maintains computer networks. They must have a strong understanding of network technologies and principles. This course may be useful for aspiring Network Administrators as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Network Administrators build and maintain reliable and scalable networks.
Web Developer
Web Developer
A Web Developer designs, develops, and maintains websites. They must have a strong understanding of web development technologies and principles. This course may be useful for aspiring Web Developers as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Web Developers build and maintain reliable and scalable websites.
Technical Writer
Technical Writer
A Technical Writer creates user manuals, technical reports, and other documentation. They must have a strong understanding of technical writing principles and practices. This course may be useful for aspiring Technical Writers as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Technical Writers create clear and concise documentation for technical products.
IT Manager
IT Manager
An IT Manager plans, implements, and manages information technology systems. They must have a strong understanding of IT management principles and practices. This course may be useful for aspiring IT Managers as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help IT Managers build and maintain reliable and scalable IT systems.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. They must have a strong understanding of project management principles and practices. This course may be useful for aspiring Project Managers as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Project Managers plan and execute projects effectively.
Data Engineer
Data Engineer
A Data Engineer focuses on developing and maintaining data pipelines. They ensure the efficient movement and transformation of data between various systems. This course may be useful for aspiring Data Engineers as it covers topics like data ingestion, stream processing, and data storage. Understanding these concepts can help Data Engineers build reliable and scalable data pipelines.
For more career information including salaries, visit:
OpenCourser.com/course/slcwtv/building
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
Building Resilient Streaming Analytics Systems on GCP en Français.
This widely recognized book on Hadoop provides a comprehensive overview of the platform, including its history, ecosystem, and applications in big data analytics.
This classic work on data warehousing offers a comprehensive guide to dimensional modeling, providing valuable background knowledge for understanding data architectures.
Offers a comprehensive overview of designing data-intensive applications, providing background knowledge and insights that support the course concepts.
Provides a practical introduction to deep learning using fastai and PyTorch, complementing the course's focus on data processing and analytics.
Provides a practical introduction to large-scale machine learning with Python, complementing the course's focus on data processing.
Provides a comprehensive overview of big data analytics with Java. It covers topics such as data ingestion, processing, and storage, and discusses various big data tools and technologies. It is more focused on the practical aspects of big data analytics than the course, and would be a valuable resource for anyone who wants to get started with this topic. It good option for someone with a Java background.
Concise overview of data analytics fundamentals. It covers the basics of data collection, storage, retrieval, and analysis.
Provides a comprehensive overview of deep learning with Python. It covers all the basics, from neural networks to deep learning applications.
Provides a comprehensive overview of machine learning with Python. It covers all the basics, from supervised learning to unsupervised learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/slcwtv/building
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Similar courses
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Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Français
Transcript
English
This course belongs to a
collection
called
Data Engineer, Big Data and ML on Google Cloud en Français. It's comprised of five courses:
- Google Cloud Big Data and Machine Learning Fundamentals en Français
- Building Resilient Streaming Analytics Systems on GCP en Français (viewing)
- Smart Analytics, Machine Learning, and AI on GCP en Français
- Modernizing Data Lakes and Data Warehouses with GCP en Français
- Building Batch Data Pipelines on GCP en Français
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