CRM-ANALYTICS-AND-EINSTEIN-DISCOVERY-CONSULTANT: SALESFORCE CERTIFIED CRM ANALYTICS AND EINSTEIN DISCOVERY CONSULTANT PREPARATION & CRM-ANALYTICS-AND-EINSTEIN-DISCOVERY-CONSULTANT PREP4SURE TORRENT

CRM-Analytics-and-Einstein-Discovery-Consultant: Salesforce Certified CRM Analytics and Einstein Discovery Consultant preparation & CRM-Analytics-and-Einstein-Discovery-Consultant prep4sure torrent

CRM-Analytics-and-Einstein-Discovery-Consultant: Salesforce Certified CRM Analytics and Einstein Discovery Consultant preparation & CRM-Analytics-and-Einstein-Discovery-Consultant prep4sure torrent

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Salesforce CRM-Analytics-and-Einstein-Discovery-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.
Topic 2
  • Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.
Topic 3
  • Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.
Topic 4
  • Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q67-Q72):

NEW QUESTION # 67
consultant is reviewing a model that is set to maximize the daily sales quantity of consumer products in stores, and they see this recommendation.

Which action should the consultant take?

  • A. Verify client expectations that Store is a strong predictor for daily sales quantity.
  • B. Ignore alert; the explanation of variation is only 35%, which is below 50%,
  • C. Remove the Store field from the model definition, because that is the recommended action.

Answer: A

Explanation:
Upon reviewing the data model and noticing the high correlation alert between 'Store' and daily sales quantity, the appropriate action is to verify with the client their expectations regarding the influence of the Store field on daily sales. Here's the rationale:
Understanding the Role of 'Store' in the Model: Before making any changes to the model, it's crucial to understand whether the 'Store' field is expected to be a strong predictor based on the business context. If the client expects that different stores inherently have different sales volumes due to factors like location, size, or customer base, this correlation may be both meaningful and desired.
Potential Data Leakage: High correlation warnings can sometimes indicate data leakage, where a predictor (like 'Store') might inadvertently include information about the outcome variable (daily sales quantity). It's essential to verify whether this correlation makes sense logically or if it's skewing the model predictions.
Client Consultation: Consulting with the client helps ensure that any modeling decisions align with their business knowledge and expectations. It's about validating the model against real-world expectations and ensuring it remains a useful tool for decision-making.
By taking these steps, the consultant not only adheres to best practices in data science by validating model inputs and their implications but also ensures that the model aligns with the client's business strategies and operational realities.


NEW QUESTION # 68
Acompany wants to create a timeline chart to visualize the evolution of its Closed Won opportunities.

What are the required parameters to build a lens that displays output similar to the image shown?

  • A. 1 measure, 1-2 groupings if trellis is disabled, or 1-4 groupings if trellis is enabled
  • B. 1 measure, 1 grouping by a date field, and either 0-1 groupings groupings by a dimensionif trellis is disabled, or 0-2groupings if trellis is enabled
  • C. 1 measure, 0 groupings if trellis Is disabled, or 0-2 groupings If trellis is enabled

Answer: B

Explanation:
To create a timeline chart similar to the one shown, the following parameters are typically required:
* 1 Measure: This could be the count of Closed Won opportunities or any other relevant metric that needs to be tracked over time.
* 1 Grouping by a Date Field: This is essential to plot the timeline effectively. The date field would typically be the close date of the opportunities.
* Additional Groupings: Depending on the complexity and the detail needed, additional groupings can be added. For example, grouping by region or product line can provide more insights into the timeline. If trellis is used, it allows for the creation of multiple smaller charts within the main chart, each representing a slice of data based on the additional groupings.
This setup helps visualize the evolution of Closed Won opportunities over time, making it easy to spot trends, seasonal patterns, or other relevant insights.


NEW QUESTION # 69
Universal Containers builds a new sales dashboard and wants to make sure account managers can access the dashboard while traveling.
What should the consultant consider doing in this process?

  • A. A Set the optimal Dashboard width for the Phone layout to get a more accurate preview.
  • B. Make sure the dashboard automatically is optimized for mobile viewing.
  • C. Enable mobile optimization in the analytics settings under Setup.

Answer: A


NEW QUESTION # 70
How many external files can be uploaded to Einstein Analytics on rolling 24 hour basis?

  • A. 500 files per dataset
  • B. 50 files Per dataset
  • C. 100 files per dataset
  • D. 300 files per dataset

Answer: B


NEW QUESTION # 71
Which of the following are included in the template object?

  • A. variables.json
  • B. ui.json
  • C. A,B and C
  • D. app.json
  • E. A,C

Answer: E

Explanation:
* template-info.json manages all elements of your template, including metadata information about the template, the Analytics objects that define dashboards and lenses, and the other files that are part of the template.
* ui.json manages the configuration wizard that drives app creation. It defines the number of wizard pages, the order of wizard questions, and any messages you want the user to see.
* variables.json contains all template variables, including text for wizard questions and specifications for the answers. Variables also define conditional questions. For example, you may want some questions to appear in the wizard only if an org contains certain data. Or you might want to add more specific questions based on the answers to more general wizard questions.
* template-to-app-rules.json defines the rules the template follows. For example, you could define a rule that specifies that if an org doesn't use certain Salesforce objects, the app won't refer to them in dashboards or include them in the dataflow. Rules also define how variables are handled. For example, if the wizard asks which fields to include in filters for accounts, template-to-app-rules.json determines how that choice is reflected in dashboards.


NEW QUESTION # 72
......

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