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Updated: Sep 14, 2026
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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Tableau CRM and Einstein Discovery Consultant |
| Exam Number: | Tableau-CRM-Einstein-Discovery-Consultant |
| Available Languages: | English |
| Real Exam Qty: | 60 |
| Related Certifications: | Salesforce Certified Tableau CRM and Einstein Discovery Consultant |
| Certificate Validity Period: | 3 years |
| Passing Score: | 65% |
| Exam Format: | Multiple Choice, Multiple Select |
| Exam Price: | USD 200 |
| Exam Duration: | 105 minutes |
| Sample Questions: | Salesforce Tableau-CRM-Einstein-Discovery-Consultant日本語 Sample Questions |
| Exam Way: | Online proctored or at a testing center |
| Pre Condition: | No formal prerequisites, but recommended to have experience with CRM Analytics implementation |
| Official Syllabus URL: | https://trailhead.salesforce.com/help?article=Salesforce-Certified-Tableau-CRM-and-Einstein-Discovery-Consultant-Exam-Guide |
| 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% | - 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 |
| Topic 3: 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 4: Einstein Discovery | 12% | - 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 - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) |
| Topic 5: Data Layer | 24% | - Data transformation and loading into Einstein datasets - Data extraction from sources - Incremental sync configuration - Understanding denormalized sequential datasets - Troubleshooting failed dataflow jobs - Dataflow configuration for multi-object scenarios |
| Topic 6: Analytics Dashboard Implementation | 19% | - Making dashboards actionable and accessible in Lightning pages - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Monitoring and optimizing query performance using Dashboard Inspector - Developing selection/result interactions with different query types - Using advanced functionality such as windowing and time series analysis in compare tables - Configuring dashboards using accurate query types and widget-level parameters |
データセットを作成するための2つの主な手順は何ですか?
Correct Answer: D 🗳️
SAQLのキーワードとは何ですか?そして、それはどのような場合に当てはまりますか?
Reveal Solution Discussion 0Correct Answer:
A keyword is basically just a function in SAQL, like group, foreach, etc. And it has to be lowercase.
「段階的開示」の原則を使用して設計することの2つの利点は何ですか?2つの答えを選択してください
Correct Answer: C,D 🗳️
Explanation: Only visible for PracticeMaterial members. You can sign-up / login (it's free).
コンサルタントは、指定されたアプリ内で、レンズを作成および保存する機能なしでダッシュボードを表示するようにユーザーを構成するように求められます。
ユーザーをアプリに追加した後、コンサルタントはこの要件を実装するためにどのアクションを実行する必要がありますか?
Correct Answer: D 🗳️
行レベルでAnalyticsデータへのアクセスをどのように制限できますか?
Correct Answer: C 🗳️
Explanation: Only visible for PracticeMaterial members. You can sign-up / login (it's free).
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