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Salesforce Certified Data Architect Sample Questions (Q41-Q46):

NEW QUESTION # 41
NTO (Northern Trail Outlets) has a complex Salesforce org which has been developed over past 5 years.
Internal users are complaining abt multiple data issues, including incomplete and duplicate data in the org.
NTO has decided to engage a data architect to analyze and define data quality standards.
Which 3 key factors should a data architect consider while defining data quality standards? Choose 3 answers:

Answer: A,B,C

Explanation:
Defining data duplication standards and rules, measuring data timeliness and consistency, and measuring data completeness and accuracy are three key factors that a data architect should consider while defining data quality standards. Defining data duplication standards and rules can help prevent or reduce duplicate records in the org by specifying criteria and actions for identifying and merging duplicates. Measuring data timeliness and consistency can help ensure that the data is up-to-date, reliable, and synchronized across different sources.
Measuring data completeness and accuracy can help ensure that the data is sufficient, relevant, and correct for the intended purposes.


NEW QUESTION # 42
An Architect needs to document the data architecture for a multi-system, enterprise Salesforce implementation.
Which two key artifacts should the Architect use? (Choose two.)

Answer: B,D

Explanation:
Option B is correct because data model is a key artifact that an architect should use to document the data architecture for a multi-system, enterprise Salesforce implementation1. Data model describes the structure and relationship of data entities within an organization2. Option C is correct because integration specification is another key artifact that an architect should use to document the data architecture for a multi-system, enterprise Salesforce implementation1. Integration specification defines the scope, requirements, design, testing, and deployment of integration solutions between Salesforce and other systems3. Option A is not correct because user stories are not key artifacts for documenting the data architecture, but agile development tools that capture the features and functionalities that users want from a system4. Option D is not correct because non-functional requirements are not key artifacts for documenting the data architecture, but quality attributes that specify how well a system performs its functions.


NEW QUESTION # 43
Universal Containers (UC) is migrating from a legacy system to Salesforce CRM, UC is concerned about the quality of data being entered by users and through external integrations.
Which two solutions should a data architect recommend to mitigate data quality issues?

Answer: A,D

Explanation:
According to the Salesforce documentation1, data quality is the measure of how well the data in Salesforce meets the expectations and requirements of the users and stakeholders. Data quality can be affected by various factors, such as data entry errors, data duplication, data inconsistency, data incompleteness, data timeliness, etc. To mitigate data quality issues, some of the recommended solutions are:
Leverage picklist and lookup fields where possible (option A). This means using fields that restrict the values or references that can be entered by the users or integrations. This can help reduce data entry errors, enforce data consistency, and improve data accuracy.
Leverage validation rules and workflows (option C). This means using features that allow defining rules and criteria to validate the data that is entered or updated by the users or integrations. This can help prevent invalid or incorrect data from being saved, and trigger actions or alerts to correct or improve the data.
Leveraging Apex to validate the format of data being entered via a mobile device (option B) is not a good solution, as it can be complex, costly, and difficult to maintain. It is better to use standard features or declarative tools that can handle data validation more effectively. Leveraging third-party AppExchange tools (option D) is also not a good solution, as it can incur additional costs and dependencies. It is better to use native Salesforce features or custom solutions that can handle data quality more efficiently.


NEW QUESTION # 44
Universal Containers has two systems. Salesforce and an on -premise ERP system. An architect has been tasked with copying Opportunity records to the ERP once they reach a Closed/Won Stage. The Opportunity record in the ERP system will be read-only for all fields copied in from Salesforce. What is the optimal real-time approach that achieves this solution?

Answer: A

Explanation:
Implementing a workflow rule that sends Opportunity data through Outbound Messaging is the optimal real-time approach that achieves the solution of copying Opportunity records to the ERP once they reach a Closed/Won Stage. A workflow rule can trigger an Outbound Message when an Opportunity record meets certain criteria, such as having a Closed/Won Stage. An Outbound Message can send data from Salesforce to an external system via SOAP API, without requiring any code. The external system can then process the data and create a read-only record in the ERP system. The other options are not optimal or real-time, as they would either require additional systems or tools, not provide real-time data synchronization, or not meet the frequency requirement


NEW QUESTION # 45
Universal Containers (UC) has an Application custom object, which has tens of millions of records created in the past 5 years. UC needs the last 5 years of data to exist in Salesforce at all times for reporting and queries.
UC is currently encountering performance issues when reporting and running queries on this Object using date ranges as filters. Which two options can be used to improve report performance?

Answer: B,C

Explanation:
Ask support to create a skinny table for Application with the necessary reporting fields. This is an option that can improve report performance by creating a custom table that contains frequently used fields and copies their values from standard or custom objects. Skinny tables are kept in sync with their source tables and are used in place of them for reports and queries4. Add custom indexes to the Date fields used for filtering the report. This is another option that can improve report performance by creating custom indexes on fields that are often used as filters or join conditions in reports and queries. Custom indexes can speed up data retrieval and reduce query execution time


NEW QUESTION # 46
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