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Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 16% | - Dataset security settings using sharing inheritance and security predicates - Implementing security settings for users, groups, and profiles - App sharing based on user and group requirements |
| Topic 2: Einstein Discovery | 12% | - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Adjusting data parameters and adding/removing data or columns to improve models - Analyzing model results and proposing data improvements - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Monitoring and interpreting Model Cards to improve or maintain model performance |
| Topic 3: Analytics Dashboard Implementation | 19% | - Developing selection/result interactions with different query types - Monitoring and optimizing query performance using Dashboard Inspector - 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 - Making dashboards actionable and accessible in Lightning pages |
| Topic 4: 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 |
| Topic 5: Administration | 16% | - SAQL query language for dashboard JSON and lens queries - Managing CRM Analytics environment and configurations - Embedding analytics in Salesforce - Understanding recipes (Data Prep) for visual ETL interface |
| Topic 6: Data Layer | 24% | - Data extraction from sources - Incremental sync configuration - Understanding denormalized sequential datasets - Troubleshooting failed dataflow jobs - Dataflow configuration for multi-object scenarios - Data transformation and loading into Einstein datasets |
Salesforce Tableau CRM Einstein Discovery Consultant (Tableau-CRM-Einstein-Discovery-Consultant日本語版) Sample Questions:
Question 1
CSVファイルをAnalyticsにアップロードするときに、[フィールド属性の編集]ページで何ができますか？
A. フィールド名を変更する
B. フィールドのフォーマットを変更する
C. フィールドのタイプを変更します
D. 上記のすべて
Question 2
テーブルの比較式では、次のコマンドで他の列を参照できます。
A. 数字（1..9）
B. 彼らの名前
C. 文字（A..Z）
D. 上記のすべて
Question 3
示す：
UniversalContainersにはSalesManagerダッシュボードがあります。図に示すようにテーブルを作成し、比較テーブルの最初の行として要約を計算する必要があります。
要約はどのように計算できますか？
A. 比較テーブルの[概要の表示]オプションを使用します。
B. 数式フィールドを追加して要約を計算します。
C. データフローにcomputeExpressionフィールドを作成して、要約を計算します。
D. 要約は標準インターフェースでは使用できないため、SAQLクエリを使用してください。
Question 4
Einstein Analyticsコンサルタントは、データ同期（レプリケーション）に関するパフォーマンスの問題について通知を受けます。コンサルタントは問題を調査し、不要なデータが同期されていると判断します。
データ同期（レプリケーション）のパフォーマンスを向上させるために、コンサルタントはどのソリューションを実装する必要がありますか？
A. 未使用のフィールドを除外するようにデータフローを変更し、関連データを抽出するためのフィルターを含めます。
B. 関連データを抽出するためのフィルターを使用して、未使用のフィールドを除外する新しいデータフローで最初からやり直します。
C. 未使用のフィールドをフィルターで削除して関連データを抽出することにより、既存のデータ同期（レプリケーション）プロセスを更新します。
D. データセットの数を減らして、データ同期（レプリケーション）のパフォーマンスを向上させます。
Question 5
データ同期を有効にできるオブジェクトの最大数
A. 100
B. 200
C. 50
D. 150
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: A | Question 4 Answer: C | Question 5 Answer: A |
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