Free Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant Practice Exam with Questions & Answers | Set: 7

In designing a dashboard for a Senior Sales Business Analyst that involves fiscal year product opportunities: D. Use charts to help users ask questions, not illustrate a conclusion. This approach encourages interactive exploration and deeper analysis of the data, enabling users to discover insights rather than just viewing predetermined outcomes. It supports a more analytical approach to data interpretation, which is essential in complex scenarios like fiscal year analysis. Reference: Salesforce Documentation on Effective Dashboard Design

https://help.salesforce.com/articleView?id=bi_dashboard_build_tips.htm &type=5

In Salesforce Tableau CRM, the limit on the number of queries that a user can execute per day is set to 50,000. This is designed to ensure optimal performance across the platform while providing sufficient capacity for users to carry out extensive data analysis throughout the day.

The scenario described where Yasmine cannot see any rows in the Seed Bank Orders dataset while Hadiqa can, likely indicates that the dataset's security predicate was set up to restrict data visibility based on user roles or attributes. Security predicates in Salesforce Tableau CRM are used to implement row-level security, ensuring that users only see data pertinent to their role or permissions within the organization. This security setup is crucial for maintaining data privacy and compliance. Reference: Salesforce Help - Row-Level Security

To address the performance issue with data sync (replication) caused by unnecessary data being synced, the consultant should:

• D: Update the existing data sync (replication) process by removing unused fields with a filter to extract relevant data. This approach minimizes the data volume being synchronized by focusing only on relevant fields and records, thereby improving the performance of the data sync processes.

In Tableau CRM (formerly Einstein Analytics), you can restrict access to data at the row level using security predicates. Security predicates are filter expressions added to datasets that dynamically restrict data access based on user attributes or record specifics. This method allows administrators to enforce data security policies directly within the dataset, ensuring that users only see data relevant and permitted to them, without altering the underlying data structure like removing rows manually or adding flags. Reference: https://help.salesforce.com/s/articleView?id=sf.bi_security_predicates.htm &type=5

Predicate is a name for a filter condition that defines row-level access to records in a dataset Example: "rowLevelSecurityFilter":"'AccountOwner' == \"$User.Name\""

Creating a regression timeseries in Salesforce Tableau CRM involves the use of the SAQL (Salesforce Analytics Query Language). Specifically, the timeseries function is used within SAQL to model and forecast data points across time. Here are the required steps:

• Partition: This argument in the timeseries function specifies how the data should be grouped. In most cases, this will be based on a time dimension such as date or month.
• Seasonality: Setting this parameter to 12 is typical for capturing yearly patterns and trends in the data.

To create a lens in Einstein Analytics that shows the total budget for each region for each month, including combinations with no data:

• A: Use a SAQL query leveraging the "fill" statement with a "partition" parameter. The "fill" function in SAQL can be used to ensure that every combination of region and month is displayed, filling in zeros where no data exists. This is essential for complete and accurate budget tracking across all regions and months.

In Einstein Analytics (Tableau CRM), the security options include:

• Inherited Security: Utilizes the existing Salesforce security model to control access.
• Row-level Security with Security Predicates: Offers granular control by restricting data visibility at the row level based on specific criteria.
• App Level Security: Manages access at the application level within Einstein Analytics.

Field-level security is not directly configurable within Einstein Analytics; instead, it's managed through the broader Salesforce security settings, affecting data visibility before it's imported into Einstein Analytics datasets. Reference: https://help.salesforce.com/s/articleView?id=sf.bi_security_overview.htm &type=5

Two benefits of designing using the "Progressive Disclosure" principle are:

• A: Improved ease of use for end users. By only displaying essential information initially and allowing users to access more detailed data as needed, dashboards become less cluttered and more user-friendly.
• D: Better dashboard performance. This design principle can also lead to better performance as less data is processed and rendered initially, speeding up load times and responsiveness.