100% PASS 2025 SALESFORCE THE BEST ANC-201: BUILDING LENSES, DASHBOARDS, AND APPS IN TABLEAU CRM VALID TEST PRACTICE

100% Pass 2025 Salesforce The Best ANC-201: Building Lenses, Dashboards, and Apps in Tableau CRM Valid Test Practice

100% Pass 2025 Salesforce The Best ANC-201: Building Lenses, Dashboards, and Apps in Tableau CRM Valid Test Practice

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The ANC-201 exam covers a wide range of topics related to Tableau CRM, including data modeling, data preparation, visualization, dashboard design, and app development. It requires a deep understanding of how to use Tableau CRM to analyze data, identify trends, and make informed decisions. Professionals who pass ANC-201 exam demonstrate that they have the skills and knowledge to create compelling visualizations, build effective dashboards, and develop custom apps that enable businesses to achieve their goals.

Salesforce ANC-201 Exam is designed to test the candidate's knowledge and skills in building lenses, dashboards, and apps in Tableau CRM. Tableau CRM, formerly known as Einstein Analytics, is a cloud-based business intelligence platform that allows organizations to analyze data and gain insights into their business operations. The ANC-201 exam is an important certification for professionals who want to demonstrate their expertise in Tableau CRM and enhance their prospects in the job market.

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Salesforce ANC-201: Building Lenses, Dashboards, and Apps in Tableau CRM exam is a valuable certification for Tableau CRM professionals. Building Lenses, Dashboards, and Apps in Tableau CRM certification exam covers various topics related to building custom lenses, creating dashboards, and designing custom apps using Tableau CRM. Building Lenses, Dashboards, and Apps in Tableau CRM certification can help professionals demonstrate their expertise in Tableau CRM and can improve their job prospects and salary potential.

Salesforce Building Lenses, Dashboards, and Apps in Tableau CRM Sample Questions (Q48-Q53):

NEW QUESTION # 48
What can a consultant accomplish in the Predictions page of a model?

  • A. Estimate the impacted business value of using Einstein Discovery.
  • B. If it is decided to follow some of the Einstein Recommendations for model improvement, see what the new model metrics would be.
  • C. Create predicted outcome value by manually selecting values for some of the predictor fields.

Answer: C

Explanation:
In the Predictions page of a model within CRM Analytics (formerly Einstein Discovery), users have the capability to interact with the model to see how different input values affect predictions. Here's a detailed look at what can be accomplished:
Manual Input of Predictor Values: Users can manually input or change values for predictor fields to see how these changes alter the predicted outcomes. This is especially useful for testing hypothetical scenarios and understanding how sensitive the model is to various inputs.
Real-Time Interaction: This functionality provides a hands-on way to explore the model's behavior, offering immediate feedback on how input variations impact predictions, which can help in refining the model or in training users on its application.
Scenario Analysis: By adjusting predictor values, users can conduct scenario analyses, which are crucial for strategic planning and decision-making.


NEW QUESTION # 49
A consultant is working with a credit card company that needs help with ongoing fraudulent transactions. The company provides a representative sample dataset for the consultant to analyze in Einstein Discovery. The story's initial assessment shows that a third-party payment app is the source of these fraudulent transactions. However, the company rejects this assessment outcome, stating they have not had a partnership with this payment app long enough for it to be a concern.
What is the recommended next step to improve the story outcome?

  • A. Ask the credit card company for a more comprehensive dataset to analyze.
  • B. Explain to the company that the story has returned unbiased results and the initial assessment is accurate.
  • C. Use the credit card company's domain knowledge and exclude the third-party payment app from the story.
  • D. Make adjustments to the story to better demonstrate that the third-party payment app is the culprit.

Answer: B


NEW QUESTION # 50
A dataset for building the Einstein Discovery story contains 72 fields that are potentially relevant predictors.
Which approach is considered best practice to assess the top predictors in order to get to a meaningful and robust model?

  • A. Build a story with a first set of predictors and assess which predictors are important to the story. Then drop the less important ones and add the predictors that were omitted in the first run and assess their impact.
  • B. This dataset is too big and cannot be used in Einstein Discovery. Request a new dataset with fewer predictors.
  • C. Build the story with all the predictors and indicate that Einstein Discovery should show the top predictors.
  • D. Go back to the data preparation and reduce the number of fields to less than 30 in order to produce a story.

Answer: A

Explanation:
Reference:
https://medium.com/@kshannon565/ea-certification-study-guide-part-3-einstein-discovery-story-design-70ffbe4666c2


NEW QUESTION # 51
What is the order of filter, limit, order and offset functions in SAQL?

  • A. Filter and order can be interchanged. Offset must be after filter/order and limit must come after offset.

Answer: A


NEW QUESTION # 52
The Universal Containers company uses Einstein Analytics to build dashboards for different departments: Sales, Service, and Marketing. Users for the same department have the same role and need to have access to the same dashboards. Dashboards for different departments use some common datasets with the same row-level security.
How can an Einstein Consultant address this need?

  • A. Create one application for each department and use roles to share applications.
  • B. Create one application for each department, put common datasets in the shared app, and use roles to share applications.
  • C. Create one application for each department, put common datasets in the shared app, and use permission sets to share applications.
  • D. Create one application for each department, put common datasets in the shared app, and use profiles to share applications.

Answer: B


NEW QUESTION # 53
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