Member since 2023
Delivery Shadowing
Earned יול 7, 2023 EDT
Case Studies
Earned יול 5, 2023 EDT
Understanding LookML in Looker
Earned מאי 4, 2023 EDT
Prepare Data for Looker Dashboards and Reports
Earned אפר 25, 2023 EDT
Google Cloud Essentials
Earned אפר 20, 2023 EDT
Build a Data Warehouse with BigQuery
Earned אפר 19, 2023 EDT
In this course, you shadow a series of client meetings led by a Looker Professional Services Consultant.
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.
In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.