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

According to this article, person accounts are designed to store information about individual people by combining certain account and contact fields into a single record. This is suitable for a large B2C retailer that needs to model the consumer account structure in Salesforce.

Analytics/BI Owners and Data Domain Stewards are appropriate roles as members of a team that makes decisions on enterprise-wide data governance. Analytics/BI Owners are responsible for defining the business requirements and metrics for data analysis and reporting, and Data Domain Stewards are responsible for defining and enforcing the data quality standards and rules for specific data domains. Salesforce Administrators and Operational Data Users are not suitable roles for this team, as they are more focused on the operational aspects of data management, such as configuration, maintenance, and usage.

According to the official Salesforce guide1, big objects are designed to store and manage massive data volumes within Salesforce without affecting performance. They can be queried by using Async SOQL or standard SOQL, and they can be accessed by using Apex, Visualforce, Lightning components, or APIs. Big objects are ideal for storing data that is used for analytics or reporting purposes, such as the reward program data. Option A is the correct answer because it allows NTO to create a custom big object in Salesforce that can store the reward program data and make it available for consumption by Einstein Analytics and Discovery. Option B is incorrect because Einstein cannot connect directly to the point of sales system to capture the reward program data. Option C is incorrect because Einstein Analytics does not support creating big objects. Option D is incorrect because custom objects are not suitable for storing large volumes of data.

To solve the issue of lack of governance in making changes to Salesforce, a data architect should recommend creating and managing a data dictionary and setting up a governance process for changes made to common objects. A data dictionary is a document that defines the metadata, structure, and relationship of each object and field in Salesforce. A governance process is a set of rules and procedures that govern how changes are proposed, reviewed, approved, and deployed in Salesforce. These measures will help NTO to maintain consistency, quality, and clarity of their data model and avoid confusion and errors among users. Option A is incorrect because adding description fields to explain why the field is used, and marking the field as required will not prevent unauthorized or unnecessary changes to Salesforce. Option C is incorrect because creating reports to identify which users are leaving blank, and using external data sources to augment the missing data will not address the root cause of the issue, which is the lack of governance in making changes to Salesforce. Option D is incorrect because creating validation rules with error messages to explain why the fields are used will not stop users from seeing new fields on their page that they are unsure of.

The two recommended options to assign Account ownership to mitigate potential performance problems are to let a “system user” own all the Account records without assigning any role to this user in Role Hierarchy, or to let a “system user” own the Account records and assign this user to the lowest-level role in the Role Hierarchy. This is because these options would reduce the number of sharing calculations and rules that need to be applied to the Account records, and improve the performance and scalability of the system34. The other options are not recommended, as they would increase the sharing complexity and overhead, and potentially expose sensitive data to unauthorized users.

Using Weekly Export to extract transactional data to on-premise systems and using Event Monitoring to extract event data to on-premise systems are two recommended approaches that would address the security requirement of UC. Weekly Export is a built-in feature that allows UC to download a zip file of their Salesforce data on a weekly basis. Event Monitoring is a tool that allows UC to access detailed information about various events that occur in their Salesforce org, such as logins, logouts, file downloads, etc.

 Clearing the role field in the generic user record and creating a role at the top of the role hierarchy and assigning it to the generic user are two measures that can help avoid performance issues while working with large number of order records. These measures can prevent data skew and lock contention that may occur when a single user owns or shares a large number of records

Evaluating a third-party AppExchange app, such as OwnBackup or Spanning, etc., for backup and archival purposes is the best approach to address the requirement of having a one-day SLA for any data loss. These apps can provide automated backups, granular restores, and compliance features that can help UC recover from any data loss or corruption scenarios.

According to the Salesforce documentation3, data quality is the measure of how well the data in Salesforce meets the expectations and requirements of the users and stakeholders. Data quality can be affected by various factors, such as data entry errors, data duplication, data inconsistency, data incompleteness, data timeliness, etc. To address the issues with data quality that affect the reliability of executive dashboards, a data architect should recommend:

Building a sales data warehouse with purpose-built data marts for dashboards and senior management reporting (option B). This means creating a separate database or system that stores and organizes sales data from Salesforce and other sources for analytical purposes. A data warehouse can provide a single source of truth for sales data and enable faster and more accurate reporting and analysis. A data mart is a subset of a data warehouse that focuses on a specific subject or business area, such as sales performance, customer segmentation, product profitability, etc. A data mart can provide tailored and relevant data for different users or groups based on their needs and interests.

Exploring third-party data providers to enrich and augment information entered in Salesforce (option C). This means using external services or tools that can validate, correct, update, and enhance the data that is entered or imported into Salesforce. This can help improve data quality and accuracy, and reduce data duplication and incompleteness.

Leveraging Salesforce features, such as validation rules, to avoid incomplete and incorrect records (option D). This means using features that allow defining rules and criteria to validate the data that is entered or updated by the users or integrations. This can help prevent invalid or incorrect data from being saved, and trigger actions or alerts to correct or improve the data.

Periodically exporting data to cleanse data and import them back into Salesforce for executive reports (option A) is not a good solution, as it can be time-consuming, error-prone, and inefficient. It may also cause data inconsistency and synchronization issues between Salesforce and other systems. Designing and implementing data-quality dashboard to monitor and act on records that are incomplete or incorrect (option E) is also not a good solution, as it can be complex, costly, and difficult to maintain. It may also not address the root causes of data quality issues or prevent them from occurring in the first place.