Data-Architect Exam Dumps - Salesforce Data-Architect Questions and Answers

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

PK Chunking is a feature of the Bulk API that allows splitting a large query into smaller batches based on the primary key of the object. This can improve the performance and avoid query timeouts when querying large data sets

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

Option A is correct because integrating Salesforce with the ERP environment is a technique to maintain data synchronization between systems1. Option C is correct because utilizing an MDM strategy to outline a single source of truth is another technique to ensure data quality and consistency across systems2. Option B is not correct because utilizing workbench to update files within systems is not a technique to maintain data synchronization, but a tool to perform data manipulation tasks3. Option D is not correct because building synchronization reports and dashboards is not a technique to maintain data synchronization, but a way to monitor and analyze data4.

 Exporting the setup audit trail can provide information about who is creating, changing, or deleting certain fields within the past four months. The setup audit trail tracks the recent setup changes that administrators and other users have made to the organization. The setup audit trail history shows up to 20 most recent changes in the Setup area, but administrators can download a report (in CSV format) of up to six months of setup history.

 Ensuring validation rules, triggers and other automation tools are disabled is the best way to mitigate any unwanted results during the import, as it prevents any errors or conflicts that may occur due to the existing logic. Ensuring duplication and matching rules are defined may not be sufficient or relevant for preventing unwanted results. Importing the data in smaller batches over a 24-hour period may not be necessary or efficient. Bulkifying the trigger to handle import leads may not be possible or desirable if the triggers were not designed to run during a data load.

Pre-go-live automated page-load testing against the Salesforce Full sandbox can help identify and resolve any performance bottlenecks or issues before deploying the solution to production. The Full sandbox is an ideal environment for performance testing as it replicates the production org in terms of data, metadata, and integrations. Stress testing against the web services hosted by the integration middleware can also help evaluate the scalability and reliability of the integration solution under high load conditions.

Indexing key fields used in report criteria can speed up the query execution and reduce the report run time. Indexes can be created by Salesforce automatically or manually by request. Creating one skinny table per report can also improve the reporting performance by storing frequently used fields in a separate table that does not include complex formulas or joins.

The correct answer is A, enable defer sharing calculations, and suspend sharing rule calculations. Defer sharing calculations and suspend sharing rule calculations are features that allow you to temporarily disable the automatic recalculation of sharing rules when you load large volumes of data. This can improve the performance and speed of your data load process by avoiding unnecessary system calculations. Loading the data through data loader, leveraging the bulk API, or enabling granular locking are also options that can help with data load times, but they do not directly address the system calculations issue.

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.