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Noah Brannon

회원 가입일: 2023

다이아몬드 리그

24585포인트
Manage Data Models in Looker 배지 Manage Data Models in Looker Earned 9월 19, 2023 EDT
Build LookML Objects in Looker 배지 Build LookML Objects in Looker Earned 9월 19, 2023 EDT
Data Catalog Fundamentals 배지 Data Catalog Fundamentals Earned 9월 19, 2023 EDT
Applying Advanced LookML Concepts in Looker 배지 Applying Advanced LookML Concepts in Looker Earned 9월 18, 2023 EDT
Create ML Models with BigQuery ML 배지 Create ML Models with BigQuery ML Earned 9월 18, 2023 EDT
Derive Insights from BigQuery Data 배지 Derive Insights from BigQuery Data Earned 9월 18, 2023 EDT
Prepare Data for Looker Dashboards and Reports 배지 Prepare Data for Looker Dashboards and Reports Earned 9월 17, 2023 EDT
Prepare Data for ML APIs on Google Cloud 배지 Prepare Data for ML APIs on Google Cloud Earned 9월 17, 2023 EDT
Developing Data Models with LookML 배지 Developing Data Models with LookML Earned 9월 16, 2023 EDT
Analyzing and Visualizing Data in Looker 배지 Analyzing and Visualizing Data in Looker Earned 9월 16, 2023 EDT
Applying Machine Learning to your Data with Google Cloud 배지 Applying Machine Learning to your Data with Google Cloud Earned 9월 15, 2023 EDT
Achieving Advanced Insights with BigQuery 배지 Achieving Advanced Insights with BigQuery Earned 9월 14, 2023 EDT
Introduction to Data Analytics on Google Cloud 배지 Introduction to Data Analytics on Google Cloud Earned 9월 14, 2023 EDT
Creating New BigQuery Datasets and Visualizing Insights 배지 Creating New BigQuery Datasets and Visualizing Insights Earned 9월 13, 2023 EDT
Exploring and Preparing your Data with BigQuery 배지 Exploring and Preparing your Data with BigQuery Earned 9월 12, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals - 한국어 배지 Google Cloud Big Data and Machine Learning Fundamentals - 한국어 Earned 9월 11, 2023 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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Complete the introductory Build LookML Objects in Looker skill badge to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements. 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 skill badge that you can share with your network.

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Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.

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In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.

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중급 Create ML Models with BigQuery ML 기술 배지 과정을 완료하면 BigQuery ML로 머신러닝 모델을 만들고 평가하여 데이터 예측을 수행할 수 있는 기술 역량을 입증할 수 있습니다. 기술 배지는 Google Cloud 제품 및 서비스 숙련도에 따라 Google Cloud에서 독점적으로 발급하는 디지털 배지로, 기술 배지 과정을 통해 대화형 실습 환경에서 지식을 적용하는 역량을 테스트할 수 있습니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크에 공유할 수 있는 기술 배지를 받을 수 있습니다.

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Complete the introductory Derive Insights from BigQuery Data skill badge to demonstrate skills in the following: write SQL queries, query public tables, load sample data into BigQuery, troubleshoot common syntax errors with the query validator in BigQuery, and create reports in Looker Studio by connecting to BigQuery data. 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 skill badge that you can share with your network.

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초급 Prepare Data for Looker Dashboards and Reports 기술 배지를 획득하여 데이터 필터링, 정렬, 피벗팅, 다른 Looker Explore의 결과 병합, 함수 및 연산자를 사용해 Looker 대시보드 보고서를 빌드하여 데이터를 분석 및 시각화하는 기술 역량을 입증하세요. 기술 배지는 Google Cloud 제품 및 서비스 숙련도에 따라 Google Cloud에서 독점적으로 발급하는 디지털 배지로, 기술 배지 과정을 통해 대화형 실습 환경에서 지식을 적용하는 역량을 테스트할 수 있습니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크에 공유할 수 있는 기술 배지를 받을 수 있습니다.

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초급 Prepare Data for ML APIs on Google Cloud 기술 배지를 완료하여 Dataprep by Trifacta로 데이터 정리, Dataflow에서 데이터 파이프라인 실행, Dataproc에서 클러스터 생성 및 Apache Spark 작업 실행, Cloud Natural Language API, Google Cloud Speech-to-Text API, Video Intelligence API를 포함한 ML API 호출과 관련된 기술 역량을 입증하세요. 기술 배지는 Google Cloud 제품 및 서비스 숙련도에 따라 Google Cloud에서 독점적으로 발급하는 디지털 배지로, 기술 배지 과정을 통해 대화형 실습 환경에서 지식을 적용하는 역량을 테스트할 수 있습니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크에 공유할 수 있는 기술 배지를 받을 수 있습니다.

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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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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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In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.

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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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This introductory course explores the basics of data analysis, including collection, storage, exploration, visualization, and sharing. This course also introduces Google Cloud's data analytics tools and services. Through video lectures, demos, quizzes, and hands-on labs, this course demonstrates how to go from raw data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started.

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.

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이 과정에서는 데이터-AI 수명 주기를 지원하는 Google Cloud 빅데이터 및 머신러닝 제품과 서비스를 소개합니다. Google Cloud에서 Vertex AI를 사용하여 빅데이터 파이프라인 및 머신러닝 모델을 빌드하는 프로세스, 문제점 및 이점을 살펴봅니다.

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