Приєднатися Увійти

Cesar Granjeno

Учасник із 2022

Бронзова ліга

Кількість балів: 500
Manage Data Models in Looker Earned лист. 8, 2022 EST
Delivery Shadowing Earned лист. 8, 2022 EST
Case Studies Earned лист. 7, 2022 EST
Technology + Beyond the UI Earned лист. 7, 2022 EST
Technology + Within the UI Earned лист. 7, 2022 EST
Table Calculations, Pivots, and Visualizations Earned лист. 7, 2022 EST
Building Reports in Looker Earned лист. 7, 2022 EST
Liquid Templates and Parameters Earned лист. 6, 2022 EST
Extends to Keep LookML DRY Earned лист. 6, 2022 EDT
Admin Roles and Folder Access Earned лист. 5, 2022 EDT
Version Control and Caching Earned лист. 5, 2022 EDT
The Modern Data Platform and LookML Earned лист. 4, 2022 EDT
Driving Data Culture and Designing Dashboards Earned лист. 3, 2022 EDT
Achieving Business Outcomes with Looker Earned жовт. 6, 2022 EDT
Looker Explained Earned серп. 28, 2022 EDT
Serverless Data Processing with Dataflow: Operations Earned черв. 21, 2022 EDT
Building Batch Data Pipelines on Google Cloud Earned черв. 16, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals - українська Earned черв. 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.

Докладніше

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

Докладніше

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.

Докладніше

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

Докладніше

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

Докладніше

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

Докладніше

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)

Докладніше

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.

Докладніше

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.

Докладніше

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.

Докладніше

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

Докладніше

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.

Докладніше

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.

Докладніше

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.

Докладніше

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.

Докладніше

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.

Докладніше

Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.

Докладніше

Під час курсу ви зможете ознайомитися з продуктами й сервісами Google Cloud для роботи з масивами даних і машинним навчанням, які підтримують життєвий цикл роботи з даними для тренування моделей штучного інтелекту. У курсі розглядаються процеси, проблеми й переваги створення конвеєру масиву даних і моделей машинного навчання з Vertex AI у Google Cloud.

Докладніше