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Sonal Awate

Date d'abonnement : 2022

Ligue de Diamant

39008 points
Référence : infrastructure Earned sept. 19, 2025 EDT
Data Warehousing for Partners: Stream Data with Pub/Sub Earned juil. 3, 2025 EDT
Data Warehousing for Partners: Cloud Data Fusion Pipelines Earned juil. 3, 2025 EDT
Data Lake Modernization on Google Cloud: Migrate Workflows Earned juil. 3, 2025 EDT
Vertex AI Search and Google Agentspace UI Configurations Earned juin 26, 2025 EDT
Vertex AI Search and Google Agentspace Analytics Earned juin 26, 2025 EDT
Google Cloud Big Data and Machine Learning Fundamentals - Français Earned juin 5, 2025 EDT
Google Docs Earned juin 5, 2025 EDT
Google Chat Earned juin 5, 2025 EDT
Oracle to Cloud Spanner Earned mai 15, 2024 EDT
Oracle to Cloud SQL for PostgreSQL Earned mai 15, 2024 EDT
Gouvernance des données Google Workspace Earned mai 3, 2024 EDT
Managing Change when Moving to Google Cloud Earned mai 3, 2024 EDT
Présentation des grands modèles de langage Earned mai 3, 2024 EDT
Introduction à l'IA responsable Earned mai 3, 2024 EDT
MySQL to Cloud Spanner Earned mai 2, 2024 EDT
Cloudera to Google Cloud Earned mai 2, 2024 EDT
BI Reporting: Looker Visualization on BigQuery Earned mai 2, 2024 EDT
Inside Track: Install, Deploy and Configure Actifio GO Solutions Earned avr. 30, 2024 EDT
PostgreSQL to Cloud SQL Earned avr. 26, 2024 EDT
Microsoft SQL Server to Cloud SQL Earned avr. 26, 2024 EDT
MySQL to Cloud SQL Earned avr. 26, 2024 EDT
Data Warehousing for Partners: Enable Google Cloud Customers Earned avr. 22, 2024 EDT
Gmail Earned avr. 22, 2024 EDT
Planning for a Google Workspace Deployment - Français Earned avr. 22, 2024 EDT
Modèles Transformer et modèle BERT Earned avr. 18, 2024 EDT
Architecture encodeur/décodeur Earned avr. 18, 2024 EDT
Mécanisme d'attention Earned avr. 18, 2024 EDT
Version Control and Caching Earned avr. 4, 2024 EDT
Driving Data Culture and Designing Dashboards Earned avr. 4, 2024 EDT
Looker Explained Earned avr. 4, 2024 EDT
The Modern Data Platform and LookML Earned avr. 4, 2024 EDT
Moderniser des lacs de données et des entrepôts de données avec Google Cloud Earned oct. 11, 2022 EDT

Si vous êtes un développeur cloud débutant et recherchez des exercices pratiques plus poussés au-delà des bases de Google Cloud, ce cours est fait pour vous. Il vous permettra d'acquérir de l'expérience pratique grâce aux ateliers qui traitent en profondeur de Cloud Storage et d'autres services applicatifs clés tels que Monitoring et Cloud Functions. Vous développerez des compétences précieuses que vous pourrez utiliser dans tous vos projets Google Cloud.

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This course explores how to implement a streaming analytics solution using Pub/Sub.

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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Cloud Data Fusion.

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Welcome to Migrate Workflows, where we discuss how to migrate Spark and Hadoop tasks and workflows to Google Cloud.

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Initial deployment of Vertex AI Search and Google Agentspace apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience. In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Google Agentspace apps.

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AI Applications provides built-in analytics for your Vertex AI Search and Google Agentspace apps. Learn what metrics are tracked and how to view them in this course.

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Ce cours présente les produits et services Google Cloud pour le big data et le machine learning compatibles avec le cycle de vie "des données à l'IA". Il explore les processus, défis et avantages liés à la création d'un pipeline de big data et de modèles de machine learning avec Vertex AI sur Google Cloud.

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With Google Docs, your documents are stored in the cloud, and you can access them from any computer or device. You create and edit documents right in your web browser; no special software is required. Even better, multiple people can work at the same time, you can see people’s changes as they make them, and every change is saved automatically. In this course, you will learn how to open Google Docs, create and format a new document, and apply a template to a new document. You will learn how to enhance your documents using a table of contents, headers and footers, tables, drawings, images, and more. You will learn how to share your documents with others. We will discuss your sharing options and examine collaborator roles and permissions. You will learn how to manage versions of your documents. Google Docs allows you to work in real time with others on the same document. You will learn how to create and manage comments and action items in your documents. We will review a few of the G…

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In this course, we introduce you to Google Chat, Google’s chat software included with Google Workspace. You will learn about messaging individuals and groups in Google Chat. You will also discover customization options, collaboration features and how Google Chat integrates with other Google Workspace products. We will explore the use of spaces in Google Chat, showing you how to create, manage, search, and join them. Additionally, you will understand the distinctions between using a space and a group chat. You also explore Google Chat apps and learn how to search for and use apps within Google Chat. Aside from course videos, you will complete hands-on activities to practice what you’ve learned. Consider inviting a colleague or two to interact with you in Google Chat as you complete the activities.

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Migration from Oracle to Cloud Spanner using HarbourBridge. This course describes an example scenario that uses sample data during the migration. This process includes using HarbourBridge for Assessment, Schema Conversion, Schema Transformation, Data Migration, and supporting tools for data validation.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Oracle to Cloud SQL using the Ora2Pg. An example scenario using sample data will be used to demonstrate the migration. Learners will complete an assessment quiz that focuses on the process of transferring schema, data and related processes to corresponding Google Cloud products.

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Ce cours apporte aux participants des compétences de gouvernance des données dans leur environnement Google Workspace. Les participants étudieront l'utilisation de règles de protection contre la perte de données dans Gmail et Drive afin de prévenir les fuites de données. Ils apprendront ensuite à utiliser Google Vault pour la conservation et la récupération des données. Ils découvriront ensuite comment configurer les régions de données et les paramètres d'exportation afin de se conformer à la réglementation. Enfin, ils verront comment classifier les données à l'aide d'étiquettes pour améliorer l'organisation et renforcer la sécurité.

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Moving to the cloud creates numerous opportunities to start working in a new way and it empowers the workforce to better collaborate and innovate. But it’s also a big change. Sometimes the success of the change hinges not on the change itself, but on how it’s managed. This course will help people managers to understand some of the key challenges associated with cloud adoption, and provide them with a verified in-the-field framework that will assist them in supporting their teams on the change journey. By addressing the human factor of moving to the cloud, organizations increase their chances of realizing business objectives and investing in their future talent.

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Ce cours de micro-apprentissage, qui s'adresse aux débutants, explique ce que sont les grands modèles de langage (LLM). Il inclut des cas d'utilisation et décrit comment améliorer les performances des LLM grâce au réglage des requêtes. Il présente aussi les outils Google qui vous aideront à développer votre propre application d'IA générative.

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Ce cours de micro-apprentissage, qui s'adresse aux débutants, explique ce qu'est l'IA responsable, souligne son importance et décrit comment Google l'implémente dans ses produits. Il présente également les sept principes de l'IA de Google.

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Migration from MySQL to Cloud Spanner using Dataflow that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from five products hosted on Cloudera or Hortonworks to corresponding Google Cloud services and hosted products. The migration solutions addressed will be: HDFS data to Google Cloud Dataproc and Cloud Storage Hive data to Cloud Dataproc and the Cloud Dataproc Metastore Hive data to Google Cloud BigQuery Impala data to Google Cloud BigQuery HBase to Google Cloud Bigtable Sample data will be used during all five migrations. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners understanding of the topics.

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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.

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Actifio GO for Google Cloud is a SaaS offering which enables powerful enterprise class backup and recovery for Google Cloud resident and on-premises workloads. Actifio now supports backup, disaster recovery and rapid database cloning of Oracle on Bare Metal Solution on Google Cloud besides other enterprise workloads including SAP HANA, SQL Server, and others. This course provides a deep dive into at the preparation and deployment of the Actifio GO solution and its constituent components. Each module contains demos and explanations of each component. The Actifio GO training was originally designed for and only made available to Google Teams, however we’ve recognized how beneficial it would be for our Partners and are now offering our Partners exclusive access to the Actifio training and products, so they can benefit from the demos and best practices and bring them to their Google Cloud Customers.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from PostgreSQL to CloudSQL using the Database Migration Service.

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This course aims to upskill Google Cloud partners to perform specific tasks of migrating data from Microsoft SQL Server to CloudSQL using the built-in replication capabilities of SQL Server. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data, and related processes to corresponding Google Cloud products. One or more challenge labs will test the learner's understanding of the topics.

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Migration from MySQL to Cloud SQL using Database Migration Service that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.

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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.

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Gmail is Google’s cloud based email service that allows you to access your messages from any computer or device with just a web browser. In this course, you’ll learn how to compose, send and reply to messages. You will also explore some of the common actions that can be applied to a Gmail message, and learn how to organize your mail using Gmail labels. You will explore some common Gmail settings and features. For example, you will learn how to manage your own personal contacts and groups, customize your Gmail Inbox to suit your way of working, and create your own email signatures and templates. Google is famous for search. Gmail also includes powerful search and filtering. You will explore Gmail’s advanced search and learn how to filter messages automatically.

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"Planning for a Google Workspace Deployment" est le dernier cours de la série "Google Workspace Administration". Dans ce cours, vous découvrirez la méthodologie et les bonnes pratiques de déploiement de Google. Vous suivrez Katelyn et Marcus lors de la planification du déploiement de Google Workspace chez Cymbal. Ils se concentreront sur les principaux aspects techniques du projet, à savoir le provisionnement, la distribution des e-mails, la migration des données et la coexistence, et identifieront la meilleure stratégie de déploiement pour chaque aspect. Vous verrez également toute l'importance de la gestion du changement lors du déploiement de Google Workspace, afin de s'assurer que les utilisateurs bénéficient d'une transition fluide vers Google Workspace et profitent des avantages de ce changement grâce à des communications, une assistance et des formations. Ce cours aborde des sujets théoriques et ne contient aucun exercice pratique. Si ce n'est pas déjà fait, veuillez annuler…

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Ce cours présente l'architecture Transformer et le modèle BERT (Bidirectional Encoder Representations from Transformers). Vous découvrirez quels sont les principaux composants de l'architecture Transformer, tels que le mécanisme d'auto-attention, et comment ils sont utilisés pour créer un modèle BERT. Vous verrez également les différentes tâches pour lesquelles le modèle BERT peut être utilisé, comme la classification de texte, les questions-réponses et l'inférence en langage naturel. Ce cours dure environ 45 minutes.

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Ce cours offre un aperçu de l'architecture encodeur/décodeur, une architecture de machine learning performante souvent utilisée pour les tâches "seq2seq", telles que la traduction automatique, la synthèse de texte et les questions-réponses. Vous découvrirez quels sont les principaux composants de l'architecture encodeur/décodeur, et comment entraîner et exécuter ces modèles. Dans le tutoriel d'atelier correspondant, vous utiliserez TensorFlow pour coder une implémentation simple de cette architecture afin de générer un poème en partant de zéro.

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Ce cours présente le mécanisme d'attention, une technique efficace permettant aux réseaux de neurones de se concentrer sur des parties spécifiques d'une séquence d'entrée. Vous découvrirez comment fonctionne l'attention et comment l'utiliser pour améliorer les performances de diverses tâches de machine learning, dont la traduction automatique, la synthèse de texte et les réponses aux questions.

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This course aims to introduce you to the basic concepts of Git: what it is and how it's used in Looker. You will also develop an in-depth knowledge of the caching process on the Looker platform, such as why they are used and why they work

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This course provides an iterative approach to plan, build, launch, and grow a modern, scalable, mature analytics ecosystem and data culture in an organization that consistently achieves established business outcomes. Users will also learn how to design and build a useful, easy-to-use dashboard in Looker. It assumes experience with everything covered in our Getting Started with Looker and Building Reports in Looker courses.

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By the end of this course, you should be able to articulate Looker's value propositions and what makes it different from other analytics tools in the market. You should also be able to explain how Looker works, and explain the standard components of successful service delivery.

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This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.

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Les lacs de données et les entrepôts de données sont les deux principaux composants des pipelines de données. Ce cours présente des cas d'utilisation de chaque type de stockage, ainsi que les détails techniques des solutions de lacs et d'entrepôts de données disponibles sur Google Cloud. Il décrit également le rôle des ingénieurs de données et les avantages d'un pipeline de données réussi sur les opérations commerciales, avant d'expliquer pourquoi il est important de procéder à l'ingénierie des données dans un environnement cloud. Il s'agit du premier cours de la série "Ingénierie des données sur Google Cloud". Après l'avoir terminé, inscrivez-vous au cours "Créer des pipelines de données en batch sur Google Cloud".

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