ML をデータ パイプラインに組み込むと、データから分析情報を抽出する能力を向上できます。このコースでは、Google Cloud でデータ パイプラインに ML を含める複数の方法について説明します。カスタマイズがほとんど、またはまったく必要ない場合のために、このコースでは AutoML について説明します。よりカスタマイズされた ML 機能については、Notebooks と BigQuery の機械学習（BigQuery ML）を紹介します。また、Vertex AI を使用して ML ソリューションを本番環境に導入する方法も説明します。
データレイクとデータ ウェアハウスを使用する従来のアプローチは効果的ですが、特に大規模な企業環境においては欠点があります。このコースでは、データ レイクハウスのコンセプトと、データ レイクハウスの作成に使用する Google Cloud プロダクトについて説明します。レイクハウス アーキテクチャは、オープン スタンダードのデータソースを使用し、データレイクとデータ ウェアハウスの優れた機能を組み合わせて、両者の欠点の多くに対処します。
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このコースでは、データから AI へのライフサイクルをサポートする Google Cloud のビッグデータと ML のプロダクトやサービスを紹介します。また、Google Cloud で Vertex AI を使用してビッグデータ パイプラインと ML モデルを作成する際のプロセス、課題、メリットについて説明します。
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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.
Dataplex を使ってみる
Earned 8月 8, 2023 EDT
Dataflow を使用したサーバーレスのデータ処理: 基礎
Earned 4月 12, 2023 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud - 日本語版
Earned 4月 10, 2023 EDT
Google Cloud でストリーミング データ パイプラインを構築する
Earned 2月 28, 2023 EST
Google Cloud でデータレイクとデータ ウェアハウスを構築する
Earned 1月 13, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals - 日本語版
Earned 7月 20, 2022 EDT
Table Calculations, Pivots, and Visualizations
Earned 7月 5, 2022 EDT
Building Reports in Looker
Earned 7月 5, 2022 EDT
Liquid Templates and Parameters
Earned 7月 4, 2022 EDT
Extends to Keep LookML DRY
Earned 6月 30, 2022 EDT
Admin Roles and Folder Access
Earned 5月 31, 2022 EDT
Version Control and Caching
Earned 5月 31, 2022 EDT
The Modern Data Platform and LookML
Earned 5月 17, 2022 EDT
Driving Data Culture and Designing Dashboards
Earned 4月 30, 2022 EDT
Achieving Business Outcomes with Looker
Earned 4月 22, 2022 EDT
Looker Explained
Earned 4月 19, 2022 EDT