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ARUL JERALD J

Participante desde 2023

Liga Ouro

24425 pontos
Enriquecer os metadados e a descoberta de dados do Lakehouse Earned Oct 22, 2024 EDT
Streaming de análises para o BigQuery Earned Oct 22, 2024 EDT
Proteger dados do Lakehouse Earned Oct 22, 2024 EDT
Monitoramento no Google Cloud Earned Oct 21, 2024 EDT
DEPRECATED Networking Fundamentals on Google Cloud Earned Oct 21, 2024 EDT
Monitorar e gerenciar recursos do Google Cloud Earned Oct 16, 2024 EDT
Integre dados do BigQuery e do Google Workspace com Apps Script Earned Oct 16, 2024 EDT
Build and Deploy a Generative AI solution using a RAG framework Earned Aug 23, 2024 EDT
Visualize Your Data in Looker Earned Aug 14, 2024 EDT
BI Reporting: Looker Visualization on BigQuery Earned Aug 14, 2024 EDT
Develop Agent Search and Conversation Applications Earned Aug 13, 2024 EDT
IA responsável: como aplicar os princípios de IA com o Google Cloud Earned Aug 13, 2024 EDT
Text Prompt Engineering Techniques Earned Aug 13, 2024 EDT
[DEPRECATED] Integrate Vertex AI Search and Conversation into Voice and Chat Apps Earned Aug 1, 2024 EDT
Preparar dados para APIs de ML no Google Cloud Earned Jun 6, 2024 EDT
Criar modelos de ML com o BigQuery ML Earned Nov 17, 2023 EST
Preparar dados para APIs de ML no Google Cloud Earned Nov 9, 2023 EST
Implementação do Cloud Load Balancing no Compute Engine Earned Nov 9, 2023 EST
Como aplicar conceitos avançados do LookML no Looker Earned Aug 31, 2023 EDT
Technology + Beyond the UI Earned Aug 31, 2023 EDT
Technology + Within the UI Earned Aug 31, 2023 EDT
Delivery Shadowing Earned Aug 31, 2023 EDT
Developing Data Models with LookML Earned Aug 31, 2023 EDT
Case Studies Earned Aug 30, 2023 EDT
Liquid Templates and Parameters Earned Aug 30, 2023 EDT
Extends to Keep LookML DRY Earned Aug 29, 2023 EDT
Version Control and Caching Earned Aug 29, 2023 EDT
Achieving Business Outcomes with Looker Earned Aug 29, 2023 EDT
Driving Data Culture and Designing Dashboards Earned Aug 28, 2023 EDT
Building Reports in Looker Earned Aug 28, 2023 EDT
Admin Roles and Folder Access Earned Aug 28, 2023 EDT
The Modern Data Platform and LookML Earned Aug 28, 2023 EDT
Gerencie modelos de dados no Looker Earned Aug 24, 2023 EDT
Noções básicas do LookML no Looker Earned Aug 24, 2023 EDT
Criar objetos do LookML no Looker Earned Aug 23, 2023 EDT
Prepare os dados para relatórios e dashboards do Looker Earned Aug 22, 2023 EDT
Table Calculations, Pivots, and Visualizations Earned Aug 21, 2023 EDT
Analyzing and Visualizing Data in Looker Earned Aug 21, 2023 EDT
Looker Explained Earned Aug 18, 2023 EDT

Conclua o curso com selo de habilidade Enriquecer os metadados e a descoberta de dados do Lakehouse para demonstrar suas habilidades com o BigQuery, o Lakehouse e o Knowledge Catalog. Nele, você cria tabelas do Lakehouse e melhora o gerenciamento e a descoberta de metadados dos dados da tabela.

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Ganhe um selo de habilidade ao concluir o curso Streaming de análises para o BigQuery, em que você usa o Pub/Sub, o Dataflow e o BigQuery juntos para transmitir dados para análise.

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Conclua o selo de habilidade introdutório Proteger dados do Lakehouse para demonstrar suas habilidades com IAM, BigQuery, Lakehouse e Data Catalog no Knowledge Catalog para criar e proteger tabelas do Lakehouse.

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Conclua o curso introdutório Monitoramento no Google Cloud e ganhe um selo de habilidade para demonstrar o que você sabe: como usar as ferramentas do Cloud Monitoring para monitorar recursos no Google Cloud.

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Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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Conclua o selo de habilidade introdutório Monitorar e gerenciar recursos do Google Cloud para demonstrar que você sabe conceder e revogar permissões do IAM; instalar agentes de monitoramento e geração de registros; criar, implantar e testar uma função do Cloud Run guiada por eventos.

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Conclua o curso introdutório com selo de habilidade Integre dados do BigQuery e do Google Workspace com Apps Script para demonstrar suas habilidades em conectar produtos do Workspace ao BigQuery usando o AppSheet.

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Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.

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This skill badge course aims to unlock the power of data visualization and business intelligence reporting with Looker, and gain hands-on experience through labs.

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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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In this quest, you’ll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud’s Vertex AI and Google Cloud databases.

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Quanto maior é o uso da inteligência artificial empresarial e do machine learning, mais importante é desenvolvê-los de maneira responsável. Para muitos, falar sobre a IA responsável pode ser mais fácil, mas colocá-la em prática é um desafio. Se você tem interesse em aprender a operacionalizar a IA responsável na sua organização, este curso é para você. Nele, você vai aprender como o Google Cloud faz isso hoje, além de analisar práticas recomendadas e lições aprendidas, a fim de criar uma base para elaborar sua própria abordagem de IA responsável.

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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.

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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.

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Conquiste o selo de habilidade introdutório Preparar dados para APIs de ML no Google Cloud para demonstrar que você é capaz de: limpar dados com o Dataprep by Trifacta, executar pipelines de dados no Dataflow, criar clusters e executar jobs do Apache Spark no Managed Service for Apache Spark e chamar APIs de ML, incluindo as APIs Cloud Natural Language, Google Cloud Speech-to-Text e Video Intelligence.

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Conclua o selo de habilidade intermediário Criar modelos de ML com o BigQuery ML para mostrar que você sabe: criar e avaliar modelos de machine learning usando o BigQuery ML para fazer previsões de dados.

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Conquiste o selo de habilidade introdutório Preparar dados para APIs de ML no Google Cloud para demonstrar que você é capaz de: limpar dados com o Dataprep by Trifacta, executar pipelines de dados no Dataflow, criar clusters e executar jobs do Apache Spark no Managed Service for Apache Spark e chamar APIs de ML, incluindo as APIs Cloud Natural Language, Google Cloud Speech-to-Text e Video Intelligence.

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Conclua o selo de habilidade introdutório Implementação do Cloud Load Balancing no Compute Engine para demonstrar que você sabe: criar e implantar máquinas virtuais no Compute Engine; configurar balanceadores de carga de rede e de aplicativo.

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Neste curso, você terá experiência prática aplicando conceitos avançados do LookML no Looker. Você vai aprender a usar o Liquid para personalizar e criar dimensões e medidas dinâmicas, criar tabelas dinâmicas derivadas em SQL e tabelas derivadas nativas personalizadas, e usar extensões para modularizar seu código LookML.

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In this course you will discover additional tools for your toolbox for working with complex deployments, building robust solutions, and delivering even more value.

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Develop technical skills beyond LookML along with basic administration for optimizing Looker instances

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In this course, you shadow a series of client meetings led by a Looker Professional Services Consultant.

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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.

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By the end of this course, you should feel confident employing technical concepts to fulfill business requirements and be familiar with common complex design patterns.

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In this course you will discover Liquid, the templating language invented by Shopify and explore how it can be used in Looker to create dynamic links, content, formatting, and more.

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Hands on course covering the main uses of extends and the three primary LookML objects extends are used on as well as some advanced usage of extends.

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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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In this course, we’ll show you how organizations are aligning their BI strategy to most effectively achieve business outcomes with Looker. We'll follow four iterative steps: Plan, Build, Launch, Grow, and provide resources to take into your own services delivery to build Looker with the goal of achieving business outcomes.

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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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This course is designed for Looker users who want to create their own ad-hoc reports. It assumes experience of everything covered in our Get Started with Looker course (logging in, finding Looks & dashboards, adjusting filters, and sending data)

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This course is designed to teach you about roles, permission sets and model sets. These are areas that are used together to manage what users can do and what they can see in Looker.

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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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Conclua o curso intermediário Gerencie modelos de dados no Looker para demonstrar que você sabe: manter a integridade do projeto do LookML, usar o SQL Runner para validar dados, seguir as práticas recomendadas do LookML, otimizar consultas e relatórios de desempenho e implementar tabelas derivadas permanentes e políticas de armazenamento em cache.

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Neste curso, você vai ter experiência prática com o LookML no Looker. Você vai aprender a escrever código LookML para criar novas dimensões e medidas, criar tabelas derivadas e juntá-las a Análises, filtrar Análises e definir políticas de armazenamento em cache no LookML.

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Conclua o selo de habilidade introdutório Criar objetos do LookML no Looker para demonstrar que você sabe: criar dimensões e métricas, visualizações e tabelas derivadas; definir filtros e tipos de métricas com base nos requisitos; atualizar dimensões e métricas; criar e refinar Análises, combinar visualizações com Análises atuais e decidir quais objetos do LookML criar com base nos requisitos de negócios.

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Conquiste o selo de habilidade introdutório Prepare os dados para relatórios e dashboards do Looker para mostrar que você sabe: filtrar, ordenar e dinamizar dados; mesclar resultados de diferentes Análises do Looker; e usar funções e operadores para criar dashboards e relatórios do Looker para análise e visualização de dados.

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This course reviews the processes for creating table calculations, pivots and visualizations

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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

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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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