Free Practice Questions for Salesforce Data-Architect Exam

Implementing a Contact Conference junction object with master detail relationship to both contact and conference_c is the correct way to model the relationship between the contact and conference objects, as it allows a many-to-many relationship between them. This means that each contact can attend multiple conferences, and each conference can be related to multiple contacts. Creating a master detail relationship field on either the contact or the conference object would create a one-to-many relationship, which does not meet the requirements. Creating a lookup relationship field on contact object would also create a one-to-many relationship, and would not enforce referential integrity.

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

Determining if any integration points create records in Salesforce, running key reports to determine what fields should be required, and reviewing the sharing model to determine impact on duplicate records are three areas of Salesforce that the architect should review before proposing any design recommendation. These areas will help to identify the sources and quality of data, the business rules and validations for data entry, and the access and visibility of data across users and roles. Reviewing the metadata xml files for redundant fields to consolidate, and exporting the setup audit trail to review what fields are being used are not necessary steps for optimizing a data stewardship engagement, as they are more related to metadata management and audit tracking.

According to Trailhead2, Customer 360 Data Manager is a feature that allows administrators to connect, reconcile, and share customer data across Salesforce orgs and external systems. Customer 360 Data Manager can sync product and pricing information from product master database to Salesforce using predefined mappings and rules, ensuring data quality and consistency. Option D is the correct answer because it suggests using Customer 360 Data Manager to sync product and pricing information from product master database to Salesforce. Option A is incorrect because building a custom integration for two-way sync of product and pricing information between product master and Salesforce can introduce data conflicts and duplication issues, as both systems can update the same data independently. Option B is incorrect because building a custom integration for one-way sync of product and pricing information from product master to Salesforce can be costly and time-consuming, as it requires custom development and maintenance. Option C is incorrect because implementing a manual process to update the products from an extract from the products master on a weekly basis can result in data latency and errors, as the products information may change more frequently than once a week.

The recommended approach to re-run the test is to refresh the full copy sandbox and re-run the data migration test. A full copy sandbox is a replica of the production Org, including all data, metadata, and attachments. Refreshing a full copy sandbox means creating a new copy of the production Org and replacing the existing sandbox. This would ensure that the test is run on a clean and up-to-date environment, without any leftover data or configuration from previous tests. Truncating or hard deleting objects would not be sufficient, because they would not remove all the data or metadata from the sandbox, and they could also affect other dependent objects or processes.

Integrating with a third-party database or service for address validation and enrichment is a scalable strategy that can improve the quality of the Account addresses by comparing them with a reliable source of data1. Leveraging Data.com Clean to clean up Account address fields with the D&B database is another scalable strategy that can automatically update and enrich Account records with verified information from Data.com2.

The correct answer is C, create a geolocation custom field to maintain this requirement. A geolocation custom field is a compound field that can store both latitude and longitude information in a single field. It also supports geolocation functions and distance calculations. Creating formula fields or custom fields for latitude and longitude separately would be inefficient and redundant. Recommending app exchange packages would not be a direct solution to the requirement.

The two features that a data architect should recommend to share records between Salesforce orgs are:

Change Data Capture (CDC): This is a feature that publishes change events for changes in Salesforce records, such as create, update, delete, and undelete operations. Change events can be subscribed by external systems or other Salesforce orgs using various tools, such as Platform Events, Streaming API, or CometD. CDC can help keep data in sync between Salesforce orgs in near real time89.

Salesforce to Salesforce (S2S): This is a feature that allows sharing records and related data with other Salesforce orgs that you partner with. You can choose which records and fields to share, and which orgs to share with. You can also accept updates from the other orgs to keep the data consistent10.

Salesforce Connect is not a good feature to share records between Salesforce orgs because it is intended for integrating external data sources with Salesforce using external objects. Federation Search is not a good feature to share records between Salesforce orgs because it is intended for searching across multiple Salesforce orgs without sharing data.

The correct answer is B. To make changes efficiently, a data architect should enable Defer Sharing Calculation prior to making sharing rule changes. This will allow the administrator to make multiple changes to sharing rules without recalculating them after each change, which can take a long time and cause failures. The sharing rules can be recalculated later when there are fewer users online or during off-peak hours. Option A is incorrect because logging a case with salesforce to make sharing rule changes will not speed up the process or prevent failures. Option C is incorrect because deleting old sharing rules and building new sharing rules will not reduce the processing time or failure rate. Option D is incorrect because logging out all users and making changes to sharing rules will disrupt the business operations and may not be feasible.

Using an ETL tool to orchestrate the migration is the best strategy for this scenario, as it can handle the data model changes, the large volume of records, and the tight timeline. Writing a script to use the Bulk API (option C) is also possible, but it would require more coding and testing effort. Using Data Loader and Data Import Wizard (option B) is not suitable for migrating three million records, as they have limitations on the batch size and the number of records per operation. Using Salesforce CLI (option D) is also not recommended for large data migration, as it is mainly designed for development and testing purposes