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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics Dashboard Implementation | 19% | - Using advanced functionality such as windowing and time series analysis in compare tables - Monitoring and optimizing query performance using Dashboard Inspector - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Making dashboards actionable and accessible in Lightning pages - Developing selection/result interactions with different query types - Configuring dashboards using accurate query types and widget-level parameters |
| Topic 2: 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 3: Administration | 16% | - SAQL query language for dashboard JSON and lens queries - Embedding analytics in Salesforce - Understanding recipes (Data Prep) for visual ETL interface - Managing CRM Analytics environment and configurations |
| Topic 4: Einstein Discovery | 12% | - Monitoring and interpreting Model Cards to improve or maintain model performance - 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) - Analyzing model results and proposing data improvements - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics |
| Topic 5: 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 |
| Topic 6: Security | 16% | - Implementing security settings for users, groups, and profiles - App sharing based on user and group requirements - Dataset security settings using sharing inheritance and security predicates |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
Question 1
1つの変数が結果変数の変動をどのように説明するかを調べる洞察のタイプの別名は何ですか？
A. スペクトル分析
B. 3次分析
C. 二次分析
D. 一次分析
E. オブジェクト指向分析
Question 2
データセットレシピで何ができますか？
A. 異なるデータセットのデータを組み合わせる
B. データチリを作る
C. ダッシュボードを作成する
D. 外部データをアナリティクスに抽出します
Question 3
Universal Containersは、リストウィジェットでの選択が、EinsteinAnalyticsダッシュボードの1つにある円グラフに影響を与えていないことを報告します。リストウィジェットと円グラフに関連付けられているステップオプションが図に示されています。
ステップが同じデータセットを使用している場合、この問題を解決するためにEinsteinコンサルタントが実装できる2つの変更はどれですか？2つの答えを選択してください
A. ステップ「Step_pie_1」で「ファセットからフィルターを適用」オプションを有効にします。
B. ステップ「Region_1」で「ファセットからフィルターを適用」オプションを有効にします。
C. ステップ「Region_1」のフィルターセクションで選択バインディングを使用します。
D. ステップ「Step_pie_1」のフィルターセクションで選択バインディングを使用します。
Question 4
分析の一環として、Yasmine、Tonya、Hadiqaはレンズを作成し、プロジェクトアプリに保存する必要があります。これを行うために必要な最小限のアプリの役割は何ですか？
A. Viewer
B. Manager
C. Editor
D. Designer
Question 5
図を参照してください。
アインシュタインは、ストーリーを改善するための推奨事項を見つけました。明らかに、同じように動作する2つの変数があります。追加情報がない場合、正しいアクションは何ですか？
A. 保持量; 取引の規模がわからないと、勝つかどうかを予測するのが難しくなります。
B. このストーリーをキャンセルして、データセットを再定義します。
C. プロモーションを保持します。これは実行可能な変数であり、これがないと、規範的なアクションを推奨できません。
D. 何もしません。それらは類似しているように見えますが、ビジネスの観点からは異なる可能性があります。
Solutions:
| Question 1 Answer: D | Question 2 Answer: A | Question 3 Answer: A,D | Question 4 Answer: C | Question 5 Answer: D |
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