Salesforce Certified Data Architect Practice Test - Questions Answers, Page 2

Creating a custom object to store a copy of the record when changed and creating a custom object to store the previous and new field values are two possible actions that an architect can perform to meet the requirement of tracking field history on 100 Opportunity fields. A custom object can store more fields and records than the standard field history tracking feature, which has a limit of 20 fields per object and 18 or 24 months of data retention. A custom object can also be used for reporting and analysis of field history data.The other options are not feasible or effective for meeting the requirement

Using Salesforce duplicate management and using validation rules on new record create and edit are two things that an architect should consider using to maintain data quality for managing Contacts. Salesforce duplicate management allows the architect to create matching rules and duplicate rules to identify, prevent, or allow duplicate records based on various criteria. Validation rules allow the architect to enforce data quality standards and business logic by displaying error messages when users try to save invalid data.The other options are not relevant or helpful for maintaining data quality

Cleaning data before importing to Salesforce and using Salesforce matching and duplicate rules are two design considerations that an architect should take to minimize data duplication when migrating legacy account data from two aging systems into Salesforce. Cleaning data before importing involves removing or correcting any inaccurate, incomplete, or inconsistent data from the source systems, as well as identifying and resolving any potential duplicates. This ensures that only high-quality and unique data is imported to Salesforce. Using Salesforce matching and duplicate rules allows the architect to define how Salesforce identifies duplicate records during import and how users can handle them. This prevents or reduces the creation of duplicate records in Salesforce and improves data quality. The other options are not effective or recommended for minimizing data duplication.

Enabling Account de-duplication by creating matching rules in Salesforce, which will mass merge duplicate Accounts, is what UC should do to ensure proper data quality for their Account records. Matching rules allow UC to define how Salesforce identifies duplicate Accounts based on various criteria, such as name, address, phone number, etc. Mass merge allows UC to merge up to 200 duplicate Accounts at a time, based on the matching rules. This simplifies and automates the process of de-duplicating Accounts and improves data quality. The other options are either more time-consuming, costly, or error-prone for ensuring proper data quality.

Utilizing a Validation Rule with a REGEX operator on Postal Code and utilizing a Validation Rule with a CONTAINS operator on address fields are two actions that Cloud Kicks should take to improve data quality for their Invoice records. A Validation Rule with a REGEX operator can check if the Postal Code field matches a specific pattern or format, such as a five-digit number or a combination of letters and numbers. A Validation Rule with a CONTAINS operator can check if the address fields contain certain values, such as valid state abbreviations or country names. These Validation Rules can prevent users from saving invalid or incomplete data and display error messages to guide them to correct the data.The other options are not effective or recommended for improving data quality, as they would either require additional customization, not enforce data standards, or not address the specific issues of missing states and incorrectly formatted postal codes

Making use of a third-party tool to help merge duplicate Contacts across Accounts and using Data.com to standardize Contact address information to help identify duplicates are two solutions that UC should implement to cleanse their data and have a single Contact across departments. A third-party tool, such as an app from the AppExchange, can provide advanced features and capabilities for finding and merging duplicate Contacts across different Accounts, based on various criteria and rules. Data.com can provide address verification and standardization services that can enhance the quality and consistency of Contact address information and make it easier to identify duplicates.The other options are not feasible or effective for cleansing the data, as they would either not work across different Accounts, not address the root cause of duplication, or not provide sufficient functionality for merging duplicates

Scheduling a weekly dashboard displaying records that are missing information to be sent to managers for review and using Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes are two approaches that an architect should recommend to enforce the new Data Quality Plan for UC's Salesforce data. Scheduling a weekly dashboard can provide a regular and visual way of monitoring the data quality and identifying any gaps or issues that need to be addressed by the managers or users. Using Workflow, Validation Rules, and Apex can provide various ways of enforcing data quality standards and business logic by automating actions, displaying error messages, or executing custom code when users create or edit records.The other options are not suitable or helpful for enforcing the Data Quality Plan, as they would either not provide real-time feedback, not prevent data quality issues, or not leverage the capabilities of Salesforce

Utilizing an app from the AppExchange to create data-quality dashboards is the approach that the architect should recommend for UC to implement a data-quality process to monitor the data that users are manually entering into the system through the Salesforce UI. An app from the AppExchange can provide ready-made or customizable dashboards that can display various metrics and indicators of data quality, such as completeness, accuracy, consistency, timeliness, etc. These dashboards can help UC to measure and evaluate their data quality performance and identify any areas that need improvement or attention. The other options are not relevant or effective for implementing a data-quality process, as they would either not address the issue of manual data entry, not provide data-quality monitoring, or not leverage the benefits of Salesforce.

Acquiring an AppExchange Lead de-duplication application and implementing Salesforce Matching and Duplicate Rules are two approaches that the manager at Cloud Kicks should take to avoid creating duplicate records when importing Leads into Salesforce. An AppExchange Lead de-duplication application can provide additional features and functionality for finding and preventing duplicate Leads during import, such as fuzzy matching, custom rules, mass merge, etc. Salesforce Matching and Duplicate Rules can allow the manager to define how Salesforce identifies duplicate Leads based on various criteria and how users can handle them during import, such as blocking, allowing, or alerting them. The other options are not feasible or effective for avoiding duplicate records, as they would either not work during import, not provide de-duplication capabilities, or require additional customization.