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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 |
| Data Layer | 24% | - Data extraction from sources - Dataflow configuration for multi-object scenarios - Understanding denormalized sequential datasets - Incremental sync configuration - Data transformation and loading into Einstein datasets - Troubleshooting failed dataflow jobs |
| Einstein Discovery | 12% | - 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 - Analyzing model results and proposing data improvements - Adjusting data parameters and adding/removing data or columns to improve models - Monitoring and interpreting Model Cards to improve or maintain model performance |
| 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 |
| Analytics Dashboard Design | 13% | - Creating dashboards following CRM Analytics best practices and UX design principles - Scoping, validating, and prioritizing dashboard design requirements - Identifying appropriate use and configuration of standard CRM Analytics templated apps |
| Analytics Dashboard Implementation | 19% | - Developing selection/result interactions with different query types - Monitoring and optimizing query performance using Dashboard Inspector - Using advanced functionality such as windowing and time series analysis in compare tables - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Making dashboards actionable and accessible in Lightning pages - Configuring dashboards using accurate query types and widget-level parameters |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
1. 示す：
上記の「なぜ起こったのか」の図に基づいて、どの2つのステートメントを決定できますか？2つの回答を選択してください
A) ドイツは平均よりもパフォーマンスは低いですが、製品がコールセンターの場合はパフォーマンスが向上します。
B) ドイツはより多くのコールセンター製品を販売しており、それは彼らが勝率を上げるのに役立ちます。
C) コールセンターは一般的にパフォーマンスの悪い製品であり、ドイツにはマイナスの影響を与える製品が他にもあるためです。
D) -2.2 Unexplainedは、データセットに関係なく、アインシュタインが説明できない影響があることを意味します。
2. アインシュタインディスカバリーストーリーのモデル品質メトリックは、4つのフォールドのGINI係数がそれぞれ0.82、0.83、0.84、および0.75であることを示しています。
コンサルタントが取るべき2つのアクションはどれですか？2つの答えを選択してください
A) ストーリーを展開する前に、全体的なGINI係数が良好であることを確認します。
B) データセットを調査して、ターゲットフィールドの外れ値と、ストーリーの上部に表示される主な予測子を確認します。
C) メトリックの変動は通常の範囲内であるため、ストーリーを展開します。
D) ストーリーをすぐに展開しないでください。また、1つのフォールドが他のフォールドよりもパフォーマンスが悪い理由を調べてください。
3. 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
4. アインシュタインディスカバリーは、それが明らかにした洞察をどのような順序で提示しますか？
A) 結果変数の最も大きな変動を昇順で説明する洞察
B) アルファベット順、昇順
C) アルファベット順、降順
D) BとD
E) 結果変数の最も大きな変動を降順で説明する洞察
5. Mosaicは最近、新しい開発コーディネーターであるZoeを採用しました。まず、ダニエルはゾーイにアインシュタイン分析プラットフォームのライセンスを付与しますが、ゾーイはまだアインシュタイン分析にアクセスできないと報告しています。何が問題なのですか？
A) Danielleは、ManageAnalytics権限を含む権限セットをZoeに付与する必要があります。
B) Danielleは、UseAnalytics権限を含む権限セットをZoeに付与する必要があります。
C) 管理者はデータフローを実行していません。
D) DanielleはEinsteinAnalyticsのZoeとMosaicアプリを共有していませんでした。
Solutions:
| Question # 1 Answer: B,C | Question # 2 Answer: A,D | Question # 3 Answer: A | Question # 4 Answer: E | Question # 5 Answer: B |
