Last Updated: Aug 10, 2026
No. of Questions: 244 Questions & Answers with Testing Engine
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| Section | Weight | Objectives |
|---|---|---|
| Data Layer | 24% | - Data extraction from sources - Dataflow configuration for multi-object scenarios - Understanding denormalized sequential datasets - Data transformation and loading into Einstein datasets - Incremental sync configuration - Troubleshooting failed dataflow jobs |
| Administration | 16% | - Understanding recipes (Data Prep) for visual ETL interface - Embedding analytics in Salesforce - SAQL query language for dashboard JSON and lens queries - Managing CRM Analytics environment and configurations |
| Analytics Dashboard Design | 13% | - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Scoping, validating, and prioritizing dashboard design requirements - Creating dashboards following CRM Analytics best practices and UX design principles |
| Analytics Dashboard Implementation | 19% | - Configuring dashboards using accurate query types and widget-level parameters - Developing selection/result interactions with different query types - Using advanced functionality such as windowing and time series analysis in compare tables - Making dashboards actionable and accessible in Lightning pages - Monitoring and optimizing query performance using Dashboard Inspector - Implementing delivery management strategies using versioning and/or Dashboard Publisher |
| 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 - Analyzing model results and proposing data improvements - 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) |
| 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 |
1. コンサルタントは、契約を更新する可能性が低い顧客を特定するために、チャーン予測モデルを作成しています。
取るべき適切な行動は何でしょうか?
A) 顧客の機密行動が含まれる可能性があるため、[チャーン理由] フィールドで [この変数には機密データが含まれています] ボックスを有効にします。
B) チャーン理由フィールドが null であるため、アクティブな顧客 (チャーンされて以来、チャーンしていない顧客) をトレーニング データセットから除外します。
C) チャーン理由フィールドをデータセットから除外します。
D) 「理由が指定されていません」としてフィールドされたチャーン理由の null を置き換えます。
2. テンプレートオブジェクトに含まれているのは次のうちどれですか?
A) A、C
B) app.json
C) A、B、C
D) variables.json
E) ui.json
3. クライアントには、7つの異なるダッシュボードで使用される2つのデータセットがあります。これらのダッシュボードのうち3つはマーケティングで使用され、4つは販売で使用されます。クライアントは、マーケティングのみがマーケティングダッシュボードにアクセスでき、セールスのみがセールスダッシュボードにアクセスできることを要求します。
どのような解決策をお勧めしますか?
A) 3つのカスタムアプリを作成します。1つは「ビューア」としてマーケティングを使用するマーケティングダッシュボード用、もう1つは販売を使用する販売ダッシュボード用です。
「ビューア」、およびマーケティングと販売が「ビューア」であるデータセット用の1つ。
B) データセットを複製し、2つのカスタムアプリを作成します。1つはマーケティングダッシュボードとマーケティングを「編集者」とするデータセット用、もう1つは販売ダッシュボードと販売を「編集者」とするデータセット用です。
C) 2つのカスタムアプリを作成します。1つは「ビューア」としてマーケティングを使用するマーケティングダッシュボード用で、もう1つは販売を使用する販売ダッシュボード用です。
「視聴者」両方のカスタムアプリへの参照としてデータセットを追加します。
D) データセット用に1つのカスタムアプリを作成し、それを「ビューア」としてマーケティングやセールスと共有します。
4. Einstein Discovery ストーリーの作成には次のことが含まれます。
A) データに関するメモの入力
B) 企業レポートからテキストをコピーして Einstein Discovery に貼り付ける
C) Einstein Analytics でデータセットを選択し、[ストーリーの作成] をクリックします。
D) Microsoft PowerPoint プレゼンテーションのアップロード
5. コンサルタントは、会社のEinsteinAnalyticsダッシュボードを作成しました。次に、会社はダッシュボードの拡張を要求し、表示する必要のある追加データを提供しました。その結果、コンサルタントはデータフローを「拡張」することを決定します。
この変換を説明するフレーズはどれですか?
A) 多対多の関係に基づいてデータを結合する
B) 右側の粒子に基づいてデータを追加します
C) ルックアップ関係としてデータを追加します(左側が最も低いグレインです)
D) SQLステートメントと同様のデータを結合します
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: C |
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