Pass the Salesforce Application Architect Data-Architect Questions and answers with ExamsMirror

Exporting in multiple batches and using PK Chunking are two steps that can help correct the issues with exporting large volumes of Order records using Informatica Cloud Loader. Exporting in multiple batches can reduce the load on the system and avoid timeouts or errors. Using PK Chunking can split a large data set into smaller chunks based on the record IDs and enable parallel processing of each chunk.

The correct answer is A, global unique customer number. A global unique customer number is a data element that can uniquely identify each customer across different systems. It can be used as a key to link customer records from different sources and enable reporting across these systems. Email address, phone number, and full name are not reliable or consistent identifiers for customers, as they can change over time or be shared by multiple customers.

The best object model to configure within SF for migrating individual customers (B2C) data from legacy systems is to leverage person account object in Salesforce. Person accounts are a special type of accounts that store information about individual people by combining certain account and contact fields into a single record4. Person accounts are useful for B2C scenarios where there is no need to associate a company name with a contact. Person accounts also support standard Salesforce features and functionality, such as leads, campaigns, reports, dashboards, etc5. Leverage custom person account object in SF is not a good option because there is no such thing as a custom person account object. Leverage custom account and contact object in SF is not a good option because it would require creating and maintaining additional objects and fields that may not be necessary or compatible with standard Salesforce features. Leverage standard account and contact object in SF is not a good option because it would require filling in dummy values for the account name field, which is mandatory for standard accounts.

According to the exam guide, one of the objectives is to "describe the use cases and considerations for using AppExchange apps and Wave Analytics"1. This implies that options A and B are both valid approaches to provide more analytical insights. Option C is not correct because weekly snapshots are used to track changes over time, not to provide advanced analytics3. Option D is not correct because setup audit trails are used to monitor changes in the setup menu, not to provide analytical insights.

Shield platform encryption is the recommended solution for encrypting sensitive patient records stored in files, as it provides encryption at rest for files and attachments, as well as standard and custom fields. Classic encryption only supports text fields with a maximum length of 175 characters, and does not encrypt files. Third-party App Exchange apps may not provide the same level of security and compliance as shield platform encryption. Storing files outside of salesforce may introduce additional complexity and latency

 Using a validation rule is the best way to ensure that all customers provide either a phone number or an email address when registering for an account, as it allows defining a formula that evaluates whether a record meets certain criteria. Using required fields may not work if both phone number and email address are required. Using an Apex class or a Process Builder may be more complex or cumbersome than using a validation rule.

Creating an external object Invoice_x with a Lookup relationship with Opportunity is the best option for modeling invoices, considering performance and data storage space. An external object allows the data to be stored in the ERP system and accessed via OData in Salesforce. This reduces the data storage consumption in Salesforce and improves the performance of queries and reports. A Lookup relationship allows the sales reps to view the invoice status and amount from the opportunity page. The other options would either consume more data storage space, require additional customization, or not provide real-time data access

  Master data management (MDM) is a solution that helps organizations manage their master data across multiple systems and ensure consistency and quality. An MDM solution can act as the customer master, with centralized integrations to other systems, to avoid data duplication and inconsistency.

According to Trailhead2, one of the best practices to increase Salesforce adoption is to migrate existing data from legacy systems or spreadsheets into Salesforce, so that users can access all their data in one place and leverage the features and functionality of Salesforce. Option B is the correct answer because it suggests defining a standard mapping and training sales users to import opportunity data from Excel files into Salesforce, which can help them transition from their old process and increase their confidence and satisfaction with Salesforce. Option A is incorrect because using the Excel connector to Salesforce does not migrate the data into Salesforce, but only syncs it between Excel and Salesforce, which can cause data inconsistency and duplication issues. Option C is incorrect because loading data in an external database and providing access to it does not increase Salesforce adoption, but rather creates another system for users to manage and switch between. Option D is incorrect because creating a chatter group and uploading all Excel files to it does not migrate the data into Salesforce, but only stores it as attachments, which cannot be used for reporting or analysis purposes.

The data architect should recommend using field metadata attributes for compliance categorization, data owner, and data sensitivity level. This will allow the SF admins to generate reports to manage compliance based on the field metadata attributes that are defined for each data element in SF. Option A is incorrect because using metadata API to extract field attribute information and use the extract to classify and build reports will require additional development effort and may not be up-to-date with the latest changes in SF. Option C is incorrect because creating a custom object and field to capture necessary compliance information and build custom reports will require additional configuration effort and may not be consistent with the actual data elements in SF. Option D is incorrect because building reports for field information, then exporting the information to classify and report for audits will require additional manual effort and may not be accurate or timely.