Manage Data Models in Looker
Earned nov 8, 2022 EST
Delivery Shadowing
Earned nov 8, 2022 EST
Case Studies
Earned nov 7, 2022 EST
Technology + Beyond the UI
Earned nov 7, 2022 EST
Technology + Within the UI
Earned nov 7, 2022 EST
Table Calculations, Pivots, and Visualizations
Earned nov 7, 2022 EST
Building Reports in Looker
Earned nov 7, 2022 EST
Liquid Templates and Parameters
Earned nov 6, 2022 EST
Extends to Keep LookML DRY
Earned nov 6, 2022 EDT
Admin Roles and Folder Access
Earned nov 5, 2022 EDT
Version Control and Caching
Earned nov 5, 2022 EDT
The Modern Data Platform and LookML
Earned nov 4, 2022 EDT
Driving Data Culture and Designing Dashboards
Earned nov 3, 2022 EDT
Achieving Business Outcomes with Looker
Earned oct 6, 2022 EDT
Looker Explained
Earned ago 28, 2022 EDT
Procesamiento de datos sin servidores con Dataflow: Operaciones
Earned jun 21, 2022 EDT
Creación de flujos de procesamiento de datos por lotes en Google Cloud
Earned jun 16, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals - Español
Earned jun 9, 2022 EDT
Complete the intermediate Manage Data Models in Looker skill badge to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies. 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 course, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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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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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 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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This course reviews the processes for creating table calculations, pivots and visualizations
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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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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 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 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 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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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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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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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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En esta última parte de la serie de cursos de Dataflow, presentaremos los componentes del modelo operativo de Dataflow. Examinaremos las herramientas y técnicas que permiten solucionar problemas y optimizar el rendimiento de las canalizaciones. Luego, revisaremos las prácticas recomendadas de las pruebas, la implementación y la confiabilidad en relación con las canalizaciones de Dataflow. Concluiremos con una revisión de las plantillas, que facilitan el ajuste de escala de las canalizaciones de Dataflow para organizaciones con cientos de usuarios. Estas clases asegurarán que su plataforma de datos sea estable y resiliente ante circunstancias inesperadas.
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Las canalizaciones de datos suelen realizarse según uno de los paradigmas extracción y carga (EL); extracción, carga y transformación (ELT), o extracción, transformación y carga (ETL). En este curso, abordaremos qué paradigma se debe utilizar para los datos por lotes y cuándo corresponde usarlo. Además, veremos varias tecnologías de Google Cloud para la transformación de datos, incluidos BigQuery, la ejecución de Spark en Dataproc, grafos de canalización en Cloud Data Fusion y procesamiento de datos sin servidores en Dataflow. Los estudiantes obtienen experiencia práctica en la compilación de componentes de canalizaciones de datos en Google Cloud con Qwiklabs.
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En este curso, aprenderás sobre los productos y servicios de macrodatos y aprendizaje automático de Google Cloud involucrados en el ciclo de vida de datos a IA. También explorarás los procesos, los desafíos y los beneficios de crear una canalización de macrodatos y modelos de aprendizaje automático con Vertex AI en Google Cloud.
Manage Data Models in Looker
Earned nov 8, 2022 EST
Delivery Shadowing
Earned nov 8, 2022 EST
Case Studies
Earned nov 7, 2022 EST
Technology + Beyond the UI
Earned nov 7, 2022 EST
Technology + Within the UI
Earned nov 7, 2022 EST
Table Calculations, Pivots, and Visualizations
Earned nov 7, 2022 EST
Building Reports in Looker
Earned nov 7, 2022 EST
Liquid Templates and Parameters
Earned nov 6, 2022 EST
Extends to Keep LookML DRY
Earned nov 6, 2022 EDT
Admin Roles and Folder Access
Earned nov 5, 2022 EDT
Version Control and Caching
Earned nov 5, 2022 EDT
The Modern Data Platform and LookML
Earned nov 4, 2022 EDT
Driving Data Culture and Designing Dashboards
Earned nov 3, 2022 EDT
Achieving Business Outcomes with Looker
Earned oct 6, 2022 EDT
Looker Explained
Earned ago 28, 2022 EDT
Procesamiento de datos sin servidores con Dataflow: Operaciones
Earned jun 21, 2022 EDT
Creación de flujos de procesamiento de datos por lotes en Google Cloud
Earned jun 16, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals - Español
Earned jun 9, 2022 EDT