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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 16% | - Dataset security settings using sharing inheritance and security predicates - App sharing based on user and group requirements - Implementing security settings for users, groups, and profiles |
| Topic 2: Data Layer | 24% | - Data transformation and loading into Einstein datasets - Incremental sync configuration - Understanding denormalized sequential datasets - Data extraction from sources - Dataflow configuration for multi-object scenarios - Troubleshooting failed dataflow jobs |
| Topic 3: Analytics Dashboard Design | 13% | - Scoping, validating, and prioritizing dashboard design requirements - Creating dashboards following CRM Analytics best practices and UX design principles - Identifying appropriate use and configuration of standard CRM Analytics templated apps |
| Topic 4: Einstein Discovery | 12% | - Adjusting data parameters and adding/removing data or columns to improve models - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Monitoring and interpreting Model Cards to improve or maintain model performance - Analyzing model results and proposing data improvements |
| Topic 5: Analytics Dashboard Implementation | 19% | - Making dashboards actionable and accessible in Lightning pages - Configuring dashboards using accurate query types and widget-level parameters - Monitoring and optimizing query performance using Dashboard Inspector - Using advanced functionality such as windowing and time series analysis in compare tables - Developing selection/result interactions with different query types - Implementing delivery management strategies using versioning and/or Dashboard Publisher |
| Topic 6: Administration | 16% | - Understanding recipes (Data Prep) for visual ETL interface - SAQL query language for dashboard JSON and lens queries - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations |
1. 会社のSalesforce組織で複数通貨が有効になっています。この会社のビジネスインテリジェンスチームは、Einstein Analyticsを使用して、データセット「OpportunityDataSet」を作成するデータフローを構築しました。このデータセットには、標準オブジェクトであるOpportunityから抽出されたデータが入力されます。抽出されたフィールドの1つは、標準フィールドの金額です。
ユーザーがEinsteinAnalyticsで「OpportunityDataSet」を調べた場合、金額の値はどの通貨で表示されますか?
A) データフローの「currency」属性に設定されている通貨
B) データセットの「currency」属性に設定されている通貨
C) 統合ユーザーの通貨で
D) 接続されたユーザーの通貨で
2. Einstein Analytics Plus Platformライセンスは、Salesforce組織に対して有効になっており、各ユーザーに割り当てられています。ただし、これらのユーザーは、AppLauncherでEinsteinAnalyticsStudioを表示できません。
この問題にどのように対処できますか?
A) EinsteinAnalyticsのユーザーとアプリを共有します。
B) アナリティクスの管理を含む権限セットにユーザーを割り当てます。
C) EinsteinAnalyticsでユーザーのユーザーアカウントを作成します。
D) UseAnalyticsを含む権限セットにユーザーを割り当てます。
3. データフロー定義の最大数(データ同期が有効になっている場合)
A) 35
B) 15
C) 55
D) 25
4. AnalyticsがSalesforceオブジェクトにアクセスするデータフローを実行する場合、どのユーザーを使用しますか?
A) 現在のユーザー
B) レコード所有者
C) システム管理者
D) 統合ユーザー
5. コンサルタントは、独立したEinstein Analyticsデータフローを使用してSalesforceオブジェクトを事前に抽出することにより、データの負荷を最適化したいと考えています。これを達成するためにどの構成を使用する必要がありますか?
A) クローン
B) データフロー
C) データ同期(レプリケーション)
D) 拡張
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: D |
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