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Updated: Jul 24, 2026
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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 2: Administration | 16% | - Embedding analytics in Salesforce - Understanding recipes (Data Prep) for visual ETL interface - Managing CRM Analytics environment and configurations - SAQL query language for dashboard JSON and lens queries |
| Topic 3: Einstein Discovery | 12% | - Analyzing model results and proposing data improvements - 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 - Adjusting data parameters and adding/removing data or columns to improve models - Monitoring and interpreting Model Cards to improve or maintain model performance |
| Topic 4: Analytics Dashboard Implementation | 19% | - Implementing delivery management strategies using versioning and/or Dashboard Publisher - 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 - Making dashboards actionable and accessible in Lightning pages - Configuring dashboards using accurate query types and widget-level parameters |
| Topic 5: Security | 16% | - Implementing security settings for users, groups, and profiles - Dataset security settings using sharing inheritance and security predicates - App sharing based on user and group requirements |
| Topic 6: Data Layer | 24% | - Data extraction from sources - Understanding denormalized sequential datasets - Dataflow configuration for multi-object scenarios - Data transformation and loading into Einstein datasets - Troubleshooting failed dataflow jobs - Incremental sync configuration |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
1. SAQL のフィルター、制限、順序、およびオフセット関数の順序は何ですか?
2. 目標に対して実現された売上高の進捗状況を追跡するのに最適なチャートタイプはどれですか？
A) フラットゲージ
B) 棒グラフ
C) 円グラフ
D) ピボットテーブル
3. マージンを調査するストーリーでは、製品グループ間の大きな違いがストーリーを支配しています。これを解決するために、アインシュタインのコンサルタントはどのような行動を取る可能性がありますか？
A) 製品グループごとにマージンを正規化します。
B) 地域ごとに別々のストーリーを実行します。
C) データセット内の極値を削除します。
D) データセットにデータを追加します。
4. Universal Containers社は、Microsoft Azure SQL Data Warehouseを使用して、営業担当者の目的に関する情報を収集しています。彼らは、Einstein Analyticsを使用して、このデータから洞察を得たいと考えています。したがって、ウェアハウスのデータをEinsteinAnalyticsデータセットに毎日自動的にロードする必要があります。また、データを変換して、会社の組織のデータとマージする必要があります。
これらの要件を満たすために使用できる3つのEinsteinAnalyticsユーザーインターフェイス機能はどれですか？3つの答えを選択してください
A) Analytics REST API
B) Excel用Einstein Analytics Connector
C) データフロー
D) MicrosoftAzureSQLデータウェアハウスコネクタ
E) レシピ
5. ファセットの魔法は何ですか？
A) 表示しているチャートの期間をシフトします。
B) 1つのグラフで何かを選択すると、その選択によって他のグラフがフィルタリングされるように、グラフがバインドされます。
C) データフローのオンとオフを切り替えます。
D) データのすべての面をひし形のグラフで表示するグラフを作成します。
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: C,D,E | Question # 5 Answer: B |
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