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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 |
| Einstein Discovery | 12% | - Adjusting data parameters and adding/removing data or columns to improve models - 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 - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) |
| Analytics Dashboard Implementation | 19% | - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Making dashboards actionable and accessible in Lightning pages - Using advanced functionality such as windowing and time series analysis in compare tables - Developing selection/result interactions with different query types - Monitoring and optimizing query performance using Dashboard Inspector - Configuring dashboards using accurate query types and widget-level parameters |
| 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 |
| Administration | 16% | - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations - SAQL query language for dashboard JSON and lens queries - Understanding recipes (Data Prep) for visual ETL interface |
| Data Layer | 24% | - Dataflow configuration for multi-object scenarios - Incremental sync configuration - Understanding denormalized sequential datasets - Troubleshooting failed dataflow jobs - Data transformation and loading into Einstein datasets - Data extraction from sources |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
1. リストウィジェットは、既存のチャートとテーブルを含むダッシュボードに追加されます。リストウィジェットがウィジェットのプロパティを使用してダッシュボードのチャートとテーブルをファセット化するには、何が当てはまる必要がありますか？
A) リスト、チャート、およびテーブルのステップは、共通の名前を共有する必要があります。
B) リスト、チャート、およびテーブルのステップは、同じデータセットを共有する必要があります。
C) チャートとテーブルのステップには、独自のリストウィジェットが必要です。
D) リスト、チャート、およびテーブルのステップは、異なるデータセットからの共通のディメンションを共有する必要があります。
2. インサイト リストでは、インサイトはどのような順序でランク付けされますか?
A) 地理空間
B) アルファベット順
C) 統計的有意性
D) 時間
E) 順序はありません
3. アナリティクスアプリとは何ですか？
A) 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
B) 組織のEinsteinAnalytics実装の青写真
C) 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
D) iPad用アナリティクス
4. デスクトップのダッシュボードレイアウト設計の承認を取得すると、EinsteinAnalyticsコンサルタントはモバイルレイアウトの設計プロセスを開始する準備が整います。
コンサルタントがレイアウトを開発する際に留意すべき3つの考慮事項は何ですか？3つの答えを選択してください
A) モバイルレイアウトに表示できないウィジェットがあります。
B) 複数のレイアウトが適格である場合、最も多くのデバイスプロパティが設定されているものが使用されます。同点の場合は、最後に定義されたレイアウトが使用されます。（逃した）
C) モバイルデバイスに適したレイアウトがない場合、エラーメッセージが表示されます。
D) モバイルデバイスに適格なレイアウトがない場合は、最初に定義されたレイアウトが使用されます。（逃した）
E) モバイル用のレイアウトは、デバイスがレイアウトパネルで設定されたすべてのデバイスプロパティを満たしている場合に使用できます。
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) データ同期（レプリケーション）
B) 拡張
C) クローン
D) データフロー
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: B,D,E | Question # 5 Answer: B |
