Salesforce Data-Architect - Salesforce Certified Data Architect (SP25)

Creating customers as Contacts and relating them to Business and Residential Accounts using the Account Contact Relationships (option A) is the best option to recommend for a single view of these customers without creating multiple customer records, as it allows the data architect to model complex relationships between customers and accounts using native Salesforce features and tools. Creating customers as Person Accounts and relating them to Business and Residential Accounts using the Account Contact relationship (option B) is not a good option, as it may create data redundancy and inconsistency, and it does not leverage the existing Contact object. Creating customers as individual objects and relating them with Accounts for Business and Residence accounts (option C) is also not a good option, as it may require more customization and maintenance effort, and it does not leverage the existing Account and Contact objects. Creating customers as Accounts for Residence Account and using Parent Account to relate Business Account (option D) is also not a good option, as it may create confusion and complexity with the account hierarchy, and it does not leverage the existing Contact object.

 Improving reporting performance by replacing the existing reports in Sales Cloud with new reports based on Analytics Cloud can avoid the time-out issues by leveraging the power and scalability of Analytics Cloud. Analytics Cloud can handle large volumes of data and provide faster and more interactive reports than Sales Cloud .

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.

Virtualizing the remaining set of data with salesforce connect and external objects is the best way to meet the requirements with minimal effort, as it allows salesforce to access data stored in Heroku Postgres without storing it in salesforce. This reduces the storage limitations and avoids data duplication. Heroku connect can bi-directionally sync data between systems, but it requires more configuration and maintenance. Making callouts to Heroku Postgres and persisting the data in salesforce may not be feasible for 1 billion records. Migrating the data to big objects may incur additional costs and require custom code to use async SOQL

The data architect should choose to implement duplicate rules in SF (Salesforce) to validate duplicates during the account creation process. Duplicate rules are a feature in Salesforce that allow users to define criteria and actions for detecting and preventing duplicate records. By creating duplicate rules for accounts, the data architect can ensure that any leads from the website or customers from the retail stores that match existing accounts in Salesforce are flagged or blocked before they are created as new accounts. This will help avoid duplicate accounts in Salesforce and maintain data quality. Option B is incorrect because implementing a MDM (Master Data Management) solution to validate the customer information before creating accounts in SF will require additional infrastructure cost and maintenance effort. Option C is incorrect because building custom search based on fields on accounts which can be matched with customer when they visit the store will require additional development effort and may not be accurate or user-friendly. Option D is incorrect because customizing account creation process to search if customer exists before creating an account will require additional configuration effort and may not be consistent or scalable.

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 three characteristics of a Skinny table that help improve report and query performance are: Skinny tables can contain frequently used fields and thereby help avoid joins. Skinny tables are kept in sync with changes to data in the source tables. Skinny tables do not include records that are available in the recycle bin. These characteristics are beneficial because they reduce the query complexity and execution time, and improve the data accuracy and freshness. For example, skinny tables can contain frequently used fields from multiple objects, such as Account and Contact, and thereby help avoid joins that can slow down queries4. Skinny tables are updated automatically when the source tables are modified, so they always reflect the latest data5. Skinny tables do not include records that are available in the recycle bin, so they only contain active records that are relevant for reports and queries.

Using scheduled batch Apex to copy aggregate information into a custom object and delete the original records can improve the performance and reduce the data storage limits by removing unnecessary data and keeping only the summary data that is needed for reporting. Configuring the Salesforce Archiving feature to archive older records and remove them from the data storage limits can also help with performance and storage issues by moving historical data to a separate system that is still accessible but does not affect the operational data

 To help uniquely identify customer across multiple systems, a data architect should recommend creating a custom field as external ID to maintain the customer ID from the MDM solution. An external ID is a custom field that has the “External ID” attribute enabled, which means that it contains unique record identifiers from a system outside of Salesforce. By using the customer ID from the MDM solution as an external ID in Salesforce CRM, Contract Management system, and Marketing solution, the data architect can ensure that each customer can be easily identified and integrated across these systems. Option A is incorrect because storing the Salesforce ID in all the solutions to identify the customer will not work if the customer records are created or updated in other systems besides Salesforce CRM. Option B is incorrect because creating a custom object that will serve as a cross reference for the customer ID will require additional configuration effort and may not be consistent with the actual customer records in each system. Option C is incorrect because creating a customer database and using this ID in all systems will require additional infrastructure cost and maintenance effort.

The data architect should recommend Lighting platform plus license type for the finance team that best meets the requirements. This license type allows users to access custom objects and run reports and dashboards on them, without accessing any sales objects. Option A is incorrect because Service Cloud license type is more suitable for customer service users who need to access cases, knowledge, and other service objects. Option B is incorrect because Sales Cloud license type is more suitable for sales users who need to access accounts, contacts, opportunities, and other sales objects. Option C is incorrect because Light Platform Start license type does not allow users to run reports and dashboards on custom objects.