Below is the answer and explanation for the question in the Salesforce Exams.

• Utilize the latest templates for the most modern look and feel. ✅
• Intentionally omit specific details so that users can do ad-hoc exploration if needed for root-cause analysis.
• Only provide the user with the level of detail they need to see, with the option to drill down deeper into more details.
• Implement strict security predicates to minimize the amount of information displayed to users.

Correct Answers

Utilize the latest templates for the most modern look and feel. ✅

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• /services/data/v##.#/analytics/projects
• /services/data/v##.#/analytics/wizard
• /services/data/v##.#/wave/apps
• /services/data/v##.#/wave/templates ✅

Correct Answers

/services/data/v##.#/wave/templates ✅

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• In the integration user’s currency
• In the currency that is set on the “currency” attribute in the dataflow
• The currency that is set on the “currency” attribute in the dataset ✅
• In the connected user’s currency

Correct Answers

The currency that is set on the “currency” attribute in the dataset ✅

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• Adjust the model to eliminate extreme values in the outcome variable. ✅
• Use SKU numbers rather than product names to increase clarity.
• Split the analysis into multiple models with each having fewer products.
• Run the model using the default variables in the Product object.

Correct Answers

Adjust the model to eliminate extreme values in the outcome variable. ✅

Explanation

While other story insights show historical data from past activities, predictions and improvements calculate statistically probable outcomes of future events. Einstein Discovery conducts predictive analysis to predict future outcomes, and prescriptive analysis to suggest ways in which to improve those predicted outcomes. Predictions and improvements come from the kind of regression and machine-learning analysis that data scientists conduct using advanced analytics and AI tools. Use predictions and improvements to interactively perform “what if” analyses on your data.
When you create a story with Insights & Predictions selected, Einstein Discovery also generates a model that it uses to produce predictions and improvements. You can think of a model as a sophisticated algorithm that accepts inputs (the values of explanatory variables in your data) and produces outputs (predictions and improvements). Therefore, a prediction is a derived value, produced by an Einstein Discovery model, that represents a possible future outcome. An improvement is a suggested action, based on prescriptive analytics, that a user can take to improve the likelihood of a desired outcome.

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• Use an external ETL tool to extract both datasets and delete records.
• Use a combination of dataflow transformations: “augment” and “filter.” ✅
• Use the dataflow transformation “delete” and set “userID” as the deletion ID.
• Use the recipe operation “delete” and set “userID” as the deletion ID.

Correct Answers

Use a combination of dataflow transformations: “augment” and “filter.” ✅

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• Bring Your Own Key is not supported.
• By default, the same keys are used to encrypt data in Tableau CRM as are used to encrypt data in Salesforce objects.
• When Tableau CRM Encryption is enabled, all newly registered datasets are encrypted at rest. ✅
  
• The customer’s org must have a Shield Platform Encryption tenant secret. ✅

Correct Answers

When Tableau CRM Encryption is enabled, all newly registered datasets are encrypted at rest. ✅
The customer’s org must have a Shield Platform Encryption tenant secret. ✅

Explanation

Is data encrypted in transit? Yes. However, encryption in transit is different from encryption at rest. This feature covers encryption at rest.
Can Tableau CRM bring in data encrypted with Shield Platform Encryption? Yes. Tableau CRM reads platform encrypted data in the same way that any user reads platform encrypted data. The data is then written and encrypted in Tableau CRM. It is not required that data be encrypted with Shield Platform Encryption to be encrypted in Tableau CRM. It is only required that a Tenant Secret exist for the org.
Can I mask my data? No. Masking data is not currently available and it does not fall under the Tableau CRM scope.
Are the keys different for Shield Platform Encryption and Tableau CRM Encryption? Yes, although Shield and Tableau CRM use the same key management technology, they use different keys. ionology
Do mobile dashboards still work with encryption? Yes. All Tableau CRM functionality, including support for mobile devices, works with encryption enabled. All data stored on mobile (mainly JSON code and thumbnails) is AES 256 encrypted. All
Is there any impact on application performance? The Tableau CRM Encryption solution is designed to have at most a minimal performance impact on your Tableau CRM application experience.

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• Grid over Bar
• Line over Bar ✅
• Line over Scatter Plot
• Line over Stacked Bar

Correct Answers

Line over Bar ✅

Explanation

Create a Horizontal Bar Chart
Use a horizontal bar chart to compare values across one or more categories. Using the auto-fit feature, you can fit a bar chart into a crowded dashboard without the necessity of long scroll bars or loss of information.
For example, create a bar chart that analyzes the average opportunity amount by opportunity owner.

1. In the explorer, click and then select the Bar chart type.
2. In the Bar Length field, add one or more measures.
3. In the Bars field, add one or more dimensions to analyze the measures by.
4. To rank the records and see the highest or lowest values, click the down arrow next to the measure and sort the results.

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• Remove the outliers as suggested by Einstein and deploy the model. ✅
• Remove the outliers as suggested by Einstein, and verify using model metrics and story insights if the quality improved.
• Discuss with the client if values below 0 and above 2,489 are so uncommon that they should perhaps be left out of the story. ✅
• Manually remove the sales below 0 (negative sales must be a data issue), but keep the large values (the more data, the better the model will be).

Correct Answers

Remove the outliers as suggested by Einstein and deploy the model. ✅
Discuss with the client if values below 0 and above 2,489 are so uncommon that they should perhaps be left out of the story. ✅

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• Add the new field to the existing dataset and use the XMD file parameters to hide the new field from users who should not have access to it.
• Create a new Account dataset containing the new field and give access to this dataset only to users who should be able to see the new field. ✅
• Add the new field to the existing dataset and use “Security Predicates” to hide it from users who should not access it.
• Add the new field to the existing dataset and activate “Sharing inheritance” in the Account object so only users who have access to the field in Salesforce will have access in Tableau CRM.

Correct Answers

Create a new Account dataset containing the new field and give access to this dataset only to users who should be able to see the new field. ✅

Explanation

When you share workbooks with others by publishing them to Tableau Server or Tableau Cloud, by default, all users who have access to the workbooks can see all of the data shown in the views. You can override this behavior by applying a type of filter that allows you to specify which data “rows” any given person signed in to the server can see in the view.

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Below is the answer and explanation for the question in the Salesforce Exams.

• Identify additional data that may have a stronger relationship with the outcome variable. ✅
  
• Rerun and update the story with a different algorithm.
• Proceed with deployment if the correlation values are sufficient.
• Edit the model accuracy settings and rerun the story. ✅

Correct Answers

Identify additional data that may have a stronger relationship with the outcome variable. ✅
Edit the model accuracy settings and rerun the story. ✅

Explanation

Einstein Discovery is known for its capability of bringing the power of analytics, machine learning, and statistical analysis to help businesses get important insights from their data quickly. But hey, that sounds like a job that a data scientist should do. While data scientists can bring the solutions to these tasks, it’s also important to remember that not all companies have a dedicated data scientist. In case your company does have one, the next question would be, what are the chances that your data scientist is preoccupied with other projects while you have a large amount of data that you need to analyze in a short amount of time?

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