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| Section | Weight | Objectives |
|---|---|---|
| Security | 16% | - Implementing security settings for users, groups, and profiles - App sharing based on user and group requirements - Dataset security settings using sharing inheritance and security predicates |
| Analytics Dashboard Implementation | 19% | - Monitoring and optimizing query performance using Dashboard Inspector - Using advanced functionality such as windowing and time series analysis in compare tables - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Making dashboards actionable and accessible in Lightning pages - Configuring dashboards using accurate query types and widget-level parameters - Developing selection/result interactions with different query types |
| Einstein Discovery | 12% | - Monitoring and interpreting Model Cards to improve or maintain model performance - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Adjusting data parameters and adding/removing data or columns to improve models - Analyzing model results and proposing data improvements - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) |
| Data Layer | 24% | - Incremental sync configuration - Understanding denormalized sequential datasets - Data transformation and loading into Einstein datasets - Data extraction from sources - Dataflow configuration for multi-object scenarios - Troubleshooting failed dataflow jobs |
| Administration | 16% | - Understanding recipes (Data Prep) for visual ETL interface - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations - SAQL query language for dashboard JSON and lens queries |
| Analytics Dashboard Design | 13% | - Scoping, validating, and prioritizing dashboard design requirements - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Creating dashboards following CRM Analytics best practices and UX design principles |
ある会社がEinsteinAnalyticsを使用して、次の2つのデータセットを作成しました。
1.「OpportunityWithAccount-データセット。アカウントデータによって拡張されたOpportunity標準オブジェクトからのデータが含まれています。
2.「CasewithAccount」データセット。これには、アカウントデータによって拡張されたCase標準オブジェクトからのデータが含まれています。
同社は、アカウントごとのオポチュニティとケースの総数を示すレンズを作成したいと考えています。コンサルタントはどのように彼らがこのレンズを作るのを手伝うことができますか?
Correct Answer: A 🗳️
コンサルタントは、ストーリーの中で重要な予測因子が何であるかを理解したいと考えています。
この情報が見つかる 2 つの場所はどこですか?
2 つの答えを選択してください
Correct Answer: C,D 🗳️
コンサルタントは、店舗での消費者製品の 1 日の販売数量を最大化するためのストーリーを作成しました。ストーリーを作成した後、コンサルティングには Einstein Discovery によってこのデータアラートが表示されます (図を参照)。
取るべき適切な行動を 2 つ挙げてください。
2 つの答えを選択してください
Correct Answer: A,D 🗳️
外部データファイルから作成されたデータセットのセキュリティ述語を設定するためのオプションではないのはどれですか?
Correct Answer: A 🗳️
テーブルの比較式では、次のコマンドで他の列を参照できます。
Correct Answer: D 🗳️
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