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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Einstein Discovery | 12% | - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Monitoring and interpreting Model Cards to improve or maintain model performance - Analyzing model results and proposing data improvements - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Adjusting data parameters and adding/removing data or columns to improve models |
| Topic 2: Analytics Dashboard Implementation | 19% | - Using advanced functionality such as windowing and time series analysis in compare tables - Configuring dashboards using accurate query types and widget-level parameters - Developing selection/result interactions with different query types - Monitoring and optimizing query performance using Dashboard Inspector - Making dashboards actionable and accessible in Lightning pages - Implementing delivery management strategies using versioning and/or Dashboard Publisher |
| Topic 3: Administration | 16% | - Embedding analytics in Salesforce - SAQL query language for dashboard JSON and lens queries - Understanding recipes (Data Prep) for visual ETL interface - Managing CRM Analytics environment and configurations |
| Topic 4: Data Layer | 24% | - Dataflow configuration for multi-object scenarios - Data transformation and loading into Einstein datasets - Incremental sync configuration - Troubleshooting failed dataflow jobs - Data extraction from sources - Understanding denormalized sequential datasets |
| Topic 5: Analytics Dashboard Design | 13% | - Creating dashboards following CRM Analytics best practices and UX design principles - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Scoping, validating, and prioritizing dashboard design requirements |
| Topic 6: 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 |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
1. コンサルタントは、複数の Salesforce Ogr を擁する企業の企業営業部門チーム向けに、非常に便利な Einstein Analytics アプリケーションを構築しました。各組織には同様のモデルがあり、企業の営業部門チームと同じ方法でデータをレビューしたいと考えています。アプリはパッケージ化されているので、他の本番組織にインストールする必要があります。
カスタム テンプレート アプリをインストールするための推奨される方法は何ですか?
A) Salesforce 管理パッケージ
B) メタデータ API
C) 変更セット
D) 残りの API
2. アナリティクスアプリとは何ですか？
A) 組織のEinsteinAnalytics実装の青写真
B) データセット、ダッシュボード、レンズ、およびデータフローのコレクション
C) Salesforceの外部で実行されるEinsteinAnalyticsプラットフォームの特殊バージョン
D) iPad用アナリティクス
3. コンサルタントがビューを入力された値で囲まれたドメインに制限できるウィジェットプロパティはどれですか？
A) カスタム範囲を追加
B) 範囲でフィルタリング
C) フィルターを追加
D) カスタムドメインを追加
4. Service Analyticsの概要ダッシュボードについて正しいのは次のうちどれですか？
A) 分析を開始するのに最適な場所です。
B) オープンケース、平均クローズ時間、最初の連絡先の解決、顧客満足度に関する主要な指標を即座に提供します。
C) 上記のすべて。
D) エージェントのパフォーマンス、チャネルレビュー、テレフォニーメトリックなど、より詳細なダッシュボードにドリルダウンできます。
E) デスクトップとモバイルで利用できます。
5. 「段階的開示」の原則を使用して設計することの2つの利点は何ですか？2つの答えを選択してください
A) ダッシュボードのパフォーマンスが向上
B) 成長が達成された場合の割引EAライセンス
C) エンドユーザーの使いやすさの向上
D) 自動条件付き書式
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: A,C |
