無與倫比的Salesforce Analytics-Con-201:Salesforce Certified CRM Analytics and Einstein Discovery Consultant資訊 -權威的Testpdf Analytics-Con-201題庫最新資訊

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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Einstein Discovery22%- Model Building & Configuration
  • 1. Select prediction type: numeric, binary, multi-class
  • 2. Prepare and assess data for modeling
  • 3. Train, evaluate, and refine models
- Deployment & Usage
  • 1. Embed predictions in dashboards and Lightning pages
  • 2. Monitor and maintain model performance
  • 3. Interpret results and recommendations
Topic 2: Analytics Administration & Deployment18%- Implementation & Maintenance
  • 1. Use Dashboard Inspector and Publisher
  • 2. Manage versioning and deployment
  • 3. Monitor and optimize query performance
Topic 3: Security & Access12%- Sharing & Permissions
  • 1. Manage user and group access
  • 2. Implement row-level security and inheritance
  • 3. Configure app, dataset, and field-level security
Topic 4: Data Layer23%- Data Sources & Integration
  • 1. Define datasets and map Salesforce objects
  • 2. Extract, load, and prepare data using Data Manager
  • 3. Use Dataflows and Recipes for transformation
- Data Management & Optimization
  • 1. Resolve data sync and refresh issues
  • 2. Optimize dataset performance
  • 3. Implement data modeling and relationships
Topic 5: Dashboard Design & Development25%- Build & Configure Dashboards
  • 1. Use SAQL for advanced queries
  • 2. Implement bindings, filters, and interactions
  • 3. Create lenses, steps, and visualizations
- Design Principles
  • 1. Design for mobile and Lightning compatibility
  • 2. Apply best practices for usability and performance

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最新的 Salesforce Consultant Analytics-Con-201 免費考試真題 (Q111-Q116):

問題 #111
Universal Containers has a dashboard for sales managers. They need to visualize the percentage of their opportunities in the pipeline in a Gauge chart. They want to customize the chart to keep track if they are below or beyond the target.

Which widget parameters should a consultant use?

答案:C

解題說明:
In the scenario described, the sales managers at Universal Containers require a Gauge chart that not only shows the current percentage of opportunities in their pipeline but also indicates whether they arebelow or beyond their set targets. The appropriate widget parameters to achieve this visualization in Salesforce CRM Analytics (formerly known as Einstein Analytics) are:
* Reference Line: This parameter is crucial for defining a specific target value on the gauge chart. It visually marks a point that represents the target goal, providing an immediate visual cue as to whether the current percentage is below or above this point.
* Markers: Markers are used to represent and highlight specific values on the gauge chart. They can be utilized to emphasize the current percentage level of the pipeline, making it instantly visible how close or far the current value is from the reference line or target.
* Conditional Formatting: This feature allows the chart to change color or style based on whether the current values meet, exceed, or fall below the target. It is a critical visual tool for quickly communicating performance against targets. Conditional formatting can be set to alter the appearance of the gauge's fill color based on whether the values are above, equal to, or below the reference line, thereby providing an intuitive visual representation of performance relative to targets.
The combination of these three parameters enables a highly effective visualization for sales managers to monitor their performance against key metrics and targets directly on their dashboards. This setup is aligned with Salesforce's best practices for creating meaningful and actionable insights within CRM dashboards, ensuring that users can easily interpret and react to the data presented.
For more details on configuring these parameters, you can refer to Salesforce documentation and specific Trailhead modules that cover dashboard creation and customization:
* Wave Analytics Explorer
* Building Lenses, Dashboards, and Apps in CRM Analytics
These resources provide in-depth training and examples to help users effectively use Salesforce CRM Analytics for a wide range of data visualization needs.


問題 #112
A dashboard designer at Cloud Kicks creates a dashboard in CRM Analytics. The designer notices fields display on the dashboard with their APIlabels, such as "AccountId.Industry", and wants to change this behavior.
The designer also notices that the fields and their order appear to randomly change when a values table is created.
What should the CRM Analytics consultant explain to help the designer?

答案:C

解題說明:
For the scenario at Cloud Kicks where fields display with their API labels and the fields in a values table seem to change order randomly, the correct approach is to modify these settings in the dataset explorer within CRM Analytics. This allows for a more intuitive display and control over how data is presented in dashboards.
Here's how these adjustments help:
* Modifying Field Labels: Changing the field labels from their API names to more user-friendly names enhances readability and user experience. This can be done directly in the dataset explorer, which affects how fields appear across all dashboards utilizing that dataset.
* Controlling Field Order: The order of fields in a values table can seem random if not explicitly set. By using the dataset explorer, a designer can specify the order in which fields appear, which then reflects consistently in the dashboard's values table.
This functionality is part of CRM Analytics' aim to provide flexible and customizable data visualization tools.
Training on these features is available through various Salesforce Trailhead modules that discuss dashboard and dataset customization techniques, providing practical insights and guided tutorials to enhance dashboard design and user interaction.
Both these explanations are consistent with best practices as outlined in Salesforce's CRM Analytics documentation and the Trailhead educational content, ensuring that users are well-equipped to leverage the full capabilities of CRM Analytics for effective data management and presentation.


問題 #113
What are various ways to incorporate blank space in a CRM Analytics dashboard?

答案:A

解題說明:
Incorporating blank space into a CRM Analytics dashboard can be achieved effectively through the following methods:
* Cell Spacing Layout Property: This allows for consistent spacing between cells, helping to create a visually organized and less cluttered dashboard.
* Increasing Dashboard Granularity via Columns: Using blank columns as a method to create deliberate space can help in visually separating different dashboard elements, enhancing readability and focus.
These methods ensure that the dashboard is not only functional but also aesthetically pleasing and easy to navigate.


問題 #114
A consultant is preparing a dataset to predict customer lifetime value and is collecting data from a questionnaire that asks for demographic information. A very small number of respondents fill in the Income box, but the consultant thinks that it is an informative column even though it only represents 1% of respondents.
What should the consultant do?

答案:A

解題說明:
Reference:CRM Analytics Recipes and Predict Missing Values


問題 #115
A manager at Cloud Kicks asks for data in a dashboard to be refreshed after the sync of an external connection to Google BigQuery.
How should the consultant accomplish this?

答案:B

解題說明:
For Cloud Kicks' requirement to refresh dashboard data synchronously with the sync of an external connection to Google BigQuery, the most efficient method is:
* Event-Based Triggers: Using CRM Analytics, you can set up recipes to run on an event-based trigger.
This ensures that the recipe (which processes the data for the dashboard) only runs after the external data sync is completed.
* Salesforce External Connection Syncs: By specifically targeting the synchronization event of the Salesforce external connection with Google BigQuery, the recipe ensures data consistency and timeliness without manual intervention.
* Automation and Efficiency: This approach minimizes latency and maximizes data freshness, aligning data processing closely with data availability, thus enhancing dashboard accuracy.


問題 #116
......

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