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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 |
| 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 |
| Data Layer | 24% | - Data extraction from sources - Troubleshooting failed dataflow jobs - Incremental sync configuration - Dataflow configuration for multi-object scenarios - Data transformation and loading into Einstein datasets - Understanding denormalized sequential datasets |
| Einstein Discovery | 12% | - 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 - 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) |
| Analytics Dashboard Implementation | 19% | - Developing selection/result interactions with different query types - Configuring dashboards using accurate query types and widget-level parameters - Using advanced functionality such as windowing and time series analysis in compare tables - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Monitoring and optimizing query performance using Dashboard Inspector - Making dashboards actionable and accessible in Lightning pages |
| Administration | 16% | - SAQL query language for dashboard JSON and lens queries - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations - Understanding recipes (Data Prep) for visual ETL interface |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
1. データアーキテクトは、データフロー変換を使用して、Salesforce のロール階層に基づく行レベルのセキュリティを実装したいと考えています。データセット階層を平準化するにはどの変換を使用する必要がありますか?
A) 平坦化変換
B) デルタ変換
C) ダイジェスト変換
D) sfdcDigest 変換
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) app.json
B) A、B、C
C) A、C
D) variables.json
E) ui.json
3. Einsteinコンサルタントは、EinsteinDiscoveryがお客様に提供した「WhyitHappened」インサイトを確認しています。顧客は結果を検証したいと考えています。コンサルタントはどのような行動を取るべきですか？
A) p値と標準偏差を確認します
B) データサイエンティストに相談して、調査結果を検証します
C) 共有およびエクスポート機能を使用して、調査結果が論理的に意味があるかどうかを顧客が判断できるようにします
D) Rコードモデルの検証結果をエクスポートして確認する方法をお客様に示します
4. ウォーターフォールグラフの海軍セクションは何を示していますか？
A) 要因の組み合わせが海軍の顧客のCLVにどのように影響するか
B) 選択した変数が海軍の顧客のモデルの他のすべての要因とどのように関連しているか
C) 海軍の顧客のCLVに影響を与える重要な要素と重要でない要素の関係
D) 個々の要因が海軍の顧客の結果に個別にどのように影響するか
5. 組織内のユーザーにAnalytics権限セットを割り当てると、SalesforceはAnalyticsPlatform権限セットライセンスをそのユーザーに自動割り当てします。
A) 偽
B) 真
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: B |
