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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.
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Messagerie sans serveur avec Pub/Sub
Ce module traite de l'utilisation de Pub/Sub pour ingérer des flux de données entrants.
Fonctionnalités de gestion de flux Dataflow
Ce module réexamine Dataflow et s'intéresse principalement à ses capacités de traitement de flux de données.
Traiter des flux haut débit avec BigQuery et Cloud Bigtable
Ce module traite de l'utilisation de BigQuery et Bigtable pour les flux de données.
Fonctionnalités et performances avancées de BigQuery
Ce module explore quelques-unes des fonctionnalités plus avancées de BigQuery.
Résumé du cours
Ce module récapitule les sujets abordés dans le cours.

Good to know

Know what's good
, what to watch for
, 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

Informative streaming analytics

Students find the information presented in this course to be very useful, especially the information on performance optimization and the capabilities of GCP to deal with streaming data. It also presents the impressive features of bigQuery.
Learners find the advanced SQL features of bigQuery to be powerful.
"also powerfull bigQuery advanced sql features"
Information on how to optimize performance is provided in this course.
"good information on performance optimization"
The capabilities of GCP to deal with streaming data are found to be impressive.
"Very impressive capabilities of GCP to deal with streaming data"
Learners find this course to be useful.
"Great and very usefull Course"

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
Reviewing data processing fundamentals will ensure a solid base to understand advanced concepts taught in the course.
Browse courses on Data Processing
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  • 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
Collaboration with peers through study groups provides opportunities to discuss concepts, clarify doubts, and reinforce your understanding.
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  • 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
Hands-on exploration of the Dataflow documentation will familiarize you with its capabilities and enhance your understanding of its role in data processing.
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  • 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
Applying data processing to solve a real-world business problem will enhance your critical thinking and problem-solving abilities.
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
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

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
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.
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
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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 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 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.

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