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

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.

A correct technique UC should use to solve the data inconsistency is to define a data taxonomy for product data and apply the taxonomy to the product data in the data warehouse. A data taxonomy is a hierarchical classification of data entities and attributes that defines their meaning, format, and relationships. A data taxonomy can help ensure consistency, accuracy, and completeness of product data across different systems and channels

Data skew occurs when a large number of child records are associated with a single parent record, or when a single user owns a large number of records. This can cause performance issues and lock contention. To avoid data skew, the data architect should limit assigning one user 10,000 records ownership, limit associating 10,000 opportunities to one account, and limit associating 10,000 records looking up to the same record

Building a customer view in Service Console with components that show website data and marketing data as mashup is the best option to fulfill the requirement with minimum development effort in Salesforce. A mashup is a technique that combines data from different sources into a single user interface. You can use Visualforce pages or Lightning components to create mashups that display data from external systems such as your website and marketing system. This way, you can provide your contact center agents with a comprehensive view of the customer information they need.

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

Salesforce Connect is a feature that allows users to access data from external sources and multiple Salesforce orgs, using either clicks or code. Salesforce Connect can provide read-only access to customer records across all NTO orgs, without replicating or storing the data in Salesforce.

According to the exam guide, one of the objectives is to "describe best practices for implementing a single-org strategy in a B2C scenario"1. This implies that option D is the best practice for loading individual consumers as contacts in Salesforce. This approach avoids creating unnecessary accounts and reduces data duplication. Option C is not correct because it creates one account per contact, which increases data volume and complexity. Options A and B are not correct because they do not leverage the standard contact object, which provides native functionality and integration with other Salesforce features.

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.

The data classification feature allows customers to classify their data in Salesforce based on two policies:

Data sensitivity level: This policy defines how sensitive the data is and what level of protection it requires. For example, high sensitivity data may require encryption or masking.

Compliance categorization policy: This policy defines how the data is regulated by various laws and standards. For example, GDPR or PCI DSS.