Salesforce Data-Architect Dumps

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

 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 .

A data quality problem that could cause customers to be called by multiple Sales Reps is having duplicate Contact records in the system. Duplicate records can result from data entry errors, data imports, or integrations with other systems. Duplicate records can lead to confusion, inefficiency, and customer dissatisfaction

Using the Consent Management Feature to validate consent provided under the person Account and Contact that is provided by the customer (option C) is the best option to implement these requirements, as it allows UC to store and manage consent preferences for Person Accounts and Contacts using native Salesforce features and tools. Configuring custom fields in Person Account and Contact to store consent provided by customers and validate consent against the fields (option A) or building Custom object to store consent information in Person Account and Contact and validate against this object before contacting customers (option B) are not good options, as they may require more customization and maintenance effort, and they do not leverage the existing Data Protection and Privacy feature. Deleting contact information from customers who have declined consent to be contacted (option D) is also not a good option, as it may cause data loss or compliance issues, and it does not allow UC to track or update consent preferences.

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.

 Loading all data after deferring sharing calculations can improve the performance and avoid locking issues when loading a large amount of time entry records into Salesforce.com. This is because deferring sharing calculations can temporarily suspend the calculation of sharing rules until all the data is loaded, and then recalculate them in one operation

The Individual object is a standard object that lets you store details about data privacy and protection preferences for person accounts, contacts, users, and leads. The Individual object can be used to implement a standard communication preference management model for NTO, with relationships to the other objects.

The recommended solution to ensure long-term performance for the customer categorization process is to implement a new picklist custom field in the Account object with Gold, Silver, and Bronze values. A picklist field is a simple and efficient way to store a predefined set of values for a record. A picklist field has the following benefits:

It allows you to easily filter, sort, and group records by their category values, which can help you analyze and segment your customers.

It does not require creating any additional objects or relationships, which can reduce the data model complexity and maintenance overhead.

It supports large data volumes and can handle millions of records without affecting performance or scalability.

 According to the exam guide, one of the objectives is to "describe how to use queryAll() or ALL ROWS keywords to access deleted records in Apex and SOQL"1. This implies that option C is the correct way to access deleted records in Salesforce. Option D is not correct because sending data to a data warehouse does not maintain the data in Salesforce. Options A and B are not correct because they do not apply to deleted records2.

Creating an aggregate custom object that summarizes the monthly and yearly values into the required format for the required reports (option D) is the fastest and most effective way for a data architect to solve the time-out issue, as it reduces the amount of data that needs to be queried and processed by the reports. Creating custom fields on opportunity and copying data from order into those custom fields (option A) is not a good solution, as it may create data redundancy and inconsistency, and it does not address the large volume of data. Extracting opportunity and order data from Salesforce and using a third-party reporting tool (option B) is also not a good solution, as it may introduce additional complexity and cost, and it does not leverage the native reporting features of Salesforce. Creating a skinny table in Salesforce and copying order and opportunity fields into it (option C) is also not a good solution, as it may not support all the reporting requirements, and it does not reduce the number of records.

 Event Monitoring is a feature that allows you to track user actions, such as logins, logouts, downloads, etc., in your Salesforce org. You can use Event Monitoring to monitor performance, usage, security, and compliance

Implicit sharing will automatically handle this sharing requirement with standard functionality, as it grants read-only access to parent accounts when users have access to child opportunities. This is also known as account-opportunity sharing3. Creating a criteria-based sharing rule (option A) or an owner-based sharing rule (option D) is not necessary, as they are used to grant additional access based on record criteria or ownership. Adding appropriate users to the account team (option C) is also not required, as it is used to grant access to specific users or groups for individual accounts.

Changing Opportunity Amount field access to Read Only for sales users field-level security (option C) is the best way to address the overwriting issue, as it prevents sales users from updating the field that is controlled by PPS, and ensures data consistency and accuracy. Creating a custom field for Opportunity amount that PSS updates separating the field sales user updates (option A) or creating a custom field for Opportunity amount that sales users update separating the field that PPS updates (option D) are not good solutions, as they may create confusion and inconsistency with the Opportunity Forecast feature. Changing PSS integration to update only Opportunity Amount field when the value is null (option B) is also not a good solution, as it may cause data loss or conflicts with the sales users’ inputs.

The best design pattern to satisfy the requirement of accessing order data from an on-premise database with REST API access without consuming SF storage limits is to use SF Connect to virtualize the data in SF and avoid storage limits. SF Connect is an integration tool that allows users to access and integrate data from external sources using external objects. External objects are similar to custom objects, except that the data resides in another system and is accessed in real time via web service callouts. SF Connect supports various adapters to connect to different types of external data sources, such as OData, cross-org, or Apex custom adapter11. Migrate and persist the data in SF to take advantage of native functionality is not a good option because it would consume SF storage limits and require data synchronization between systems. Develop a bidirectional integration between the on-premise system and Salesforce is not a good option because it would be complex and costly to implement and maintain, and it would also consume SF storage limits. Build a UI for the on-premise system and iframe it in Salesforce is not a good option because it would not provide a seamless user experience and it would not allow users to search, report, or perform actions on the external data.

The two solutions that a data architect should recommend to preserve the date timestamps and ownership on records being migrated are:

Enable update records with Inactive Owners Permission: This permission allows users to update record owner and sharing-based records with inactive owners. This can help preserve the original ownership of records that belong to users who are no longer active in Salesforce8.

Enable Set Audit fields upon Record Creation Permission: This permission allows users to set audit fields (such as Created By or Last Modified By) when they create a record via API importing tools like Data Loader. This can help preserve the original date timestamps of records that were created or modified in another system9.

Log a case with SF to update these fields is not a good solution because it is not necessary or feasible to ask Salesforce support to update these fields manually or programmatically. Enable modify all and view all permission is not a good solution because it does not affect the ability to preserve the date timestamps and ownership on records, but rather grants users access to all records regardless of sharing settings

According to the official Salesforce guide1, using Bulk API serial mode for data migration can help avoid locking issues by processing batches in a single thread. This mode ensures that batches are processed in the order they are received and that only one batch is processed at a time. This reduces the risk of lock contention and deadlocks, especially when updating parent and child records in a lookup relationship. Option B is the correct answer because it suggests using Bulk API serial mode for data migration. Option A is incorrect because using Bulk API parallel mode for data migration can cause locking issues by processing batches in multiple threads. This mode does not guarantee the order of batch processing and can result in concurrent updates to the same records, which can lead to lock contention and deadlocks. Option C is incorrect because inserting the order in another custom object and using Batch Apex to move the records to Service_Order__c object adds unnecessary complexity and overhead to the data migration process. Option D is incorrect because changing the lookup configuration to “Clear the value of this field” when lookup record is deleted does not address the locking issues caused by data migration, but rather by record deletion.

Creating a report in an external system combining Salesforce Account data and Invoice data from the ERP, and creating a Visualforce page combining Salesforce Account data and Invoice external object data are two approaches that an architect can suggest for achieving this solution. Both of these approaches can display data from both Accounts and Invoices in one place, using either an external reporting tool or a custom web page. Creating a report combining data from the Account standard object and the Invoices external object is not possible because Salesforce does not support reporting on external objects. Creating a separate Salesforce report for Accounts and Invoices and combining them in a dashboard is not ideal because it will not show the data in one report, but rather in two separate components.

 Creating a custom object related to the Invoice object with a picklist field for the Type allows the architect to categorize the attachments and report on them by Type. The standard Attachment object does not have a ContentType picklist field, and adding a custom picklist field to it would not be best practice.

Both A and B are automated approaches to purge detailed transactional records from Salesforce and aggregate them at a summary level1. You can use a third-party integration tool (ETL) or schedulable batch Apex to perform these tasks. Option C is not correct because a third-party business intelligence system does not purge data from Salesforce, but only analyzes it. Option D is not correct because Apex triggers are not automated, but execute when a record is inserted, updated, deleted, or undeleted.

The best Salesforce Shield capabilities for the customer are to restrict access to SF from users outside specific geography, implement transaction security policies to prevent export of SF data, and encrypt sensitive customer information maintained in SF. Salesforce Shield is a set of security features that help protect enterprise data on the Salesforce platform. It includes three components: Event Monitoring, Platform Encryption, and Field Audit Trail. Restricting access to SF from users outside specific geography can be done using network-based security features, such as IP whitelisting or VPN. Transaction security policies can be used to define actions or notifications based on user behavior patterns, such as exporting data or logging in from an unknown device. Platform Encryption can be used to encrypt data at rest using a tenant secret key that is controlled by the customer.

The two best practices that should be followed when using SOSL for searching are: Keep searches specific and avoid wildcards where possible. Use Find in “ALL FIELDS” for faster searches. These best practices are helpful because they optimize the search performance and relevance. For example, keeping searches specific and avoiding wildcards where possible can reduce the number of results returned and improve the search accuracy. Using Find in “ALL FIELDS” for faster searches can leverage Salesforce’s pre-defined indexes on common fields and return results more quickly than specifying individual fields.

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.

 Ensuring validation rules, triggers and other automation tools are disabled is the best way to mitigate any unwanted results during the import, as it prevents any errors or conflicts that may occur due to the existing logic. Ensuring duplication and matching rules are defined may not be sufficient or relevant for preventing unwanted results. Importing the data in smaller batches over a 24-hour period may not be necessary or efficient. Bulkifying the trigger to handle import leads may not be possible or desirable if the triggers were not designed to run during a data load.

 Using validation rules to mitigate this problem is the best option. Validation rules can help you prevent invalid data from being entered in your web order form. You can use validation rules to check for data quality, format, range, or consistency. For example, you can use validation rules to ensure that the order quantity is positive, the product code is valid, or the shipping address is complete.

Contacting Salesforce to enable Defer Sharing Rules is the feature that would ensure that performance, when moving Sales Reps between regions, remains adequate while meeting existing requirements. Defer Sharing Rules allows you to defer sharing rule recalculation when you make changes to public groups or roles that are used in sharing rules. This can improve performance and avoid locking issues when you move users between groups or roles2. Implementing data archiving for old Shipment records will not help with the performance issue related to sharing rules. Contacting Salesforce to create Skinny tables on Shipment will not help with the performance issue related to sharing rules. Configuring shipment OWD to Public Read/Write will not meet the existing requirements of having a Private sharing model.

Ensuring the lead data is preprocessed for quality before loading into Salesforce is the best way to maintain data quality2. Activating validation rules after the load or developing a custom Apex batch process may not catch all the errors or may require additional time and resources. Allowing validation rules to be activated during the load may cause failures or delays.

The best way to implement the storage of master key within Salesforce is to store it on the contact object as an external ID field for referential imports. This way, the data architect can use the master key as a unique identifier to match records from different systems and avoid duplicates. The other options are not feasible because they either require additional storage or do not support referential imports.

 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 correct answer is A. To provide additional guidance for users when they enter information in a standard field, a data architect should provide custom help text under field properties. This will display a help icon next to the field label that users can hover over to see the help text. Option B is incorrect because creating a custom page with help text for user guidance will require additional development effort and may not be easily accessible by users. Option C is incorrect because adding custom help text in default value for the field will overwrite the actual default value of the field and may confuse users. Option D is incorrect because adding a label field with help text adjacent to the custom field will clutter the page layout and may not be visible to users.

According to the Salesforce documentation1, reporting performance can be affected by various factors, such as the volume and complexity of data, the design and configuration of reports and dashboards, the number and type of users accessing the reports, etc. To improve reporting performance, some of the recommended solutions are:

Move data off of the platform and run reporting outside Salesforce, and give access to reports (option C). This means using an external service or tool that can extract, transform, and load (ETL) data from Salesforce to another system or database, such as a data warehouse or a business intelligence platform. This can improve reporting performance by reducing the load and latency on Salesforce, and enabling faster and more flexible reporting and analysis on the external system. Users can access the reports from the external system using a link or an embedded component in Salesforce.

Contact Salesforce support to enable skinny table for cases (option B). This means requesting Salesforce to create a custom table that contains a subset of fields from the Case object that are frequently used or queried. A skinny table can improve reporting performance by avoiding joins between standard and custom fields, omitting soft-deleted records, and leveraging indexes on the fields2.

Create a custom object to store aggregate data and run reports (option A). This means creating a custom object that contains summary or calculated data from the Case object, such as counts, sums, averages, etc. A custom object can improve reporting performance by reducing the number of records and fields that need to be queried and displayed.

Build reports using custom Lightning components (option D). This means creating custom components that use Lightning Web Components or Aura Components frameworks to display report data in Salesforce. A custom component can improve reporting performance by using client-side caching, pagination, lazy loading, or other techniques to optimize data rendering and interaction.

The Sforce-Enable-PKChunking header enables you to extract large data sets from Salesforce by using a technique called primary key (PK) chunking. PK chunking splits your query into multiple queries based on the record IDs of the queried object. This reduces the query time and avoids the query timeout issues that can occur with large data volumes

The recommended data model for consumer account data to be stored in Salesforce is to use the Account object with Person Accounts and a new B2C page layout. Person Accounts are a special type of accounts that allow you to store information about individual consumers who are not associated with a business account2. Person Accounts have the following advantages3:

They allow you to use the same standard objects and features that you use for business accounts, such as contacts, opportunities, cases, etc.

They enable you to create different page layouts and record types for B2C and B2B customers, which allows you to customize the user interface and business logic for each segment.

They support large data volumes and can scale up to 50 million records or more, which meets the expected growth of consumers over the next five years.

Ask support to create a skinny table for Application with the necessary reporting fields. This is an option that can improve report performance by creating a custom table that contains frequently used fields and copies their values from standard or custom objects. Skinny tables are kept in sync with their source tables and are used in place of them for reports and queries4. Add custom indexes to the Date fields used for filtering the report. This is another option that can improve report performance by creating custom indexes on fields that are often used as filters or join conditions in reports and queries. Custom indexes can speed up data retrieval and reduce query execution time

 Patients as Person Accounts, Payment providers as Accounts, & Doctors as Person Accounts is the optimal selection by the data architect to map the actor to Salesforce objects. This is because Person Accounts are a special type of accounts that can store both business and personal information for individual customers. Payment providers are organizations that pay for the care of patients, so they can be modeled as Accounts. Doctors are also individuals who provide care plans for patients and need access to patient information, so they can also be modeled as Person Accounts.

To build a custom big object to support storing more than 100 million records in Salesforce, a data architect should use Metadata API or Big Object in setup. Metadata API is an API that allows developers to create, retrieve, update, or delete metadata components in Salesforce programmatically. Big Object in setup is a user interface that allows admins to create big objects declaratively without writing code. Both tools can be used to define custom big objects and their fields, indexes, and relationships in Salesforce. Option A is incorrect because DX (Developer Experience) is a set of tools that allows developers to create and manage applications on Salesforce Platform, but it does not support creating big objects directly. Option D is incorrect because Object Manager in setup is a user interface that allows admins to create and manage standard and custom objects in Salesforce, but it does not support creating big objects declaratively.

The setup audit trail tracks changes made in your org’s setup area for the past 180 days1. You can export the setup audit trail and find the fields in question by filtering by action type, user, or date2.

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.

 Identifying a location to store archived data and using scheduled batch jobs to migrate and purge the aged data on a nightly basis can be a way to meet the requirements for an archive solution. The article provides a use case of how to use Heroku Connect, Postgres, and Salesforce Connect to archive old data, free up space in the org, and still retain the option to unarchive the data if needed. The article also explains how this solution can improve Salesforce performance and meet data retention policies.

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

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.

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 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

  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.

Implementing duplicate rules (option D) is the best solution to remediate the duplication issue, as it allows the data architect to identify and merge duplicate accounts in Salesforce using native features and tools. Developing an ETL process that utilizes the merge API to merge the duplicate records (option A) is not a good solution, as it may require more coding and testing effort, and it does not prevent duplicates from being created in Salesforce. Utilizing a data warehouse as the system of truth (option B) is also not a good solution, as it may introduce additional complexity and cost, and it does not address the duplication issue in Salesforce. Extracting the data using data loader and using excel to merge the duplicate records (option C) is also not a good solution, as it may be time-consuming and error-prone, and it does not prevent duplicates from being created in Salesforce.

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.

Using third-party AppExchange tools to monitor and measure data quality can address the requirement of UC executives by providing features such as data cleansing, deduplication, validation, enrichment, and scoring. These tools can help improve the accuracy, completeness, and consistency of the data entered by sales reps .

To improve the performance of SOQL queries that retrieve data from the Order_c object, the data architect should work with Salesforce Support to enable Skinny Tables and make the queries more selective using indexed fields. Skinny Tables are custom tables that contain frequently used fields and are kept in sync with the base tables3. They can improve performance by reducing the number of table joins and using indexes. Making the queries more selective using indexed fields can also improve performance by reducing the query execution time and avoiding query timeouts4. The other options are not effective or recommended for improving SOQL performance.

Leveraging a “tier”-based approach to classify the record storage need is a true statement with respect to a data archiving strategy for UC. This approach involves defining different tiers of data based on their usage, value, and retention policies, and then applying appropriate storage and archiving solutions for each tier.

Setting up a Validation Rule to prevent blank values and marking the field required in setup at the field level are two approaches that the Architect should take to ensure that the field always contains data coming from the source system. A Validation Rule can display an error message when a record is created or edited with a blank value for the field, and prevent it from being saved. Marking the field required in setup at the field level can enforce the requirement for all records, regardless of the page layout or the source system. The other options are not effective or recommended for ensuring data quality, as they would either not prevent blank values, not apply to all records, or not address the root cause of the problem

Key stakeholders from both systems should collaborate with the Architect to determine which system is the system of record on a field level is what the Architect should do to achieve this goal of integrating two different systems with customer records into the Salesforce Account object using Master Data Management. The system of record is the authoritative source of truth for a given entity or field in a given context. Different systems may have different levels of accuracy, completeness, timeliness, or relevance for different fields. Therefore, it is important to involve key stakeholders from both systems who have knowledge and expertise about their data quality and business needs to decide which system should be the system of record for each field. The Architect should facilitate this collaboration and document the decisions and rationale for each field. The other options are not correct or feasible, as they would either delegate or abdicate the responsibility of determining the system of record, ignore or disregard the input from key stakeholders, or assume or impose a default system of record without considering the data quality and business needs.

 Skinny tables are custom tables that contain frequently used fields from a standard or custom object. They are used to improve performance by reducing the number of database joins required for queries. Skinny tables have the following characteristics1:

They do not include soft-deleted records, which means they only contain active records and save space.

They avoid resource intensive joins by storing data from multiple objects in one table, which reduces the query time and complexity.

Their tables are kept in sync with their source tables when the source tables are modified, which ensures data consistency and accuracy.

According to the Salesforce documentation1, the query plan tool is a tool that can be enabled and used in the developer console to analyze the performance of a SOQL query. The query plan tool shows the cost, cardinality, sObject type, and relative cost of each query plan that Salesforce considers for a query. The relative cost indicates how expensive a query plan is compared to the Force.com query optimizer threshold. A query plan with a relative cost above 1.0 is likely to cause a time-out error.

To identify why the query is taking too long, a data architect should use the query plan tool in the developer console (option B). This way, the data architect can see which query plan is chosen by Salesforce and how it affects the performance of the query. The data architect can also use the query plan tool to optimize the query by adding indexes, filters, or limits to reduce the cost and improve the efficiency of the query.

Using Splunk to query the system logs looking for transaction time and CPU usage (option A) is not a good solution, as it can be complex, costly, and difficult to integrate with Salesforce. It may also not provide enough information or insights to identify and optimize the query performance. Using Salesforce’s query optimizer to analyze the query in the developer console (option C) is also not a good solution, as it is not a separate tool that can be used in the developer console. The query optimizer is a feature that runs automatically when a SOQL query is executed and chooses the best query plan based on various factors2. Opening a ticket with Salesforce support to retrieve transaction logs to be analyzed for processing time (option D) is also not a good solution, as it can be time-consuming, dependent, and inefficient. It may also not provide enough information or insights to identify and optimize the query performance.

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 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.

 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.

Checking if the current user is NOT the owner by creating a “before delete” trigger can meet the requirement of allowing only the owner of a contact record to delete that contact. A trigger is a piece of Apex code that can execute before or after a record is inserted, updated, deleted, or undeleted. A “before delete” trigger can prevent the deletion of a record by using the addError() method.

The number of joins used in report query and the number of records returned by report query are two key considerations to make sure the performance of the report is not degraded due to large data volume. The number of joins used in report query affects the complexity and execution time of the query, especially when joining multiple large objects4. The number of records returned by report query affects the amount of data that needs to be processed and displayed by the report engine.

Exploring external data sources in Salesforce to build a 360 degree view of the customer (option A) is the best strategy to satisfy this requirement, as it allows customer service agents to view the activities from all four systems in real time without storing or replicating the data in Salesforce. Using a customer data mart to create the 360 degree view of the customer (option B) is not a good strategy, as it may introduce additional complexity and cost, and it does not leverage the native Salesforce features. Periodically uploading summary information in Salesforce to build a 360 degree view (option C) is also not a good strategy, as it may cause data latency and inconsistency, and it does not provide real-time information. Migrating customer activities from all four systems into Salesforce (option D) is also not a good strategy, as it may cause data redundancy and conflicts, and it does not scale well with large volumes of data.

The recommended solution to address the requirements of Universal Containers (UC) is to roll-up discount request amount at the line-item-level and line-item-level summary discount at the opportunity level. This solution would allow UC to show all sums of discounts across line items at an opportunity level using standard roll-up summary fields. Since UC has a multi-level master-detail relationship for opportunities, a custom opportunity line item object, and a custom discount request object, they can use two levels of roll-up summary fields to aggregate the discount amounts from the child objects to the parent objects. For example, they can create a roll-up summary field on the custom line item object to sum up the discount request amounts from the custom discount request object. Then, they can create another roll-up summary field on the opportunity object to sum up the line-item-level summary discounts from the custom line item object.

Utilizing an app from the AppExchange to create data-quality dashboards is the approach that the architect should recommend for UC to implement a data-quality process to monitor the data that users are manually entering into the system through the Salesforce UI. An app from the AppExchange can provide ready-made or customizable dashboards that can display various metrics and indicators of data quality, such as completeness, accuracy, consistency, timeliness, etc. These dashboards can help UC to measure and evaluate their data quality performance and identify any areas that need improvement or attention. The other options are not relevant or effective for implementing a data-quality process, as they would either not address the issue of manual data entry, not provide data-quality monitoring, or not leverage the benefits of Salesforce.

Option B is the most appropriate approach for data archiving in this scenario1. By aggregating order amount data at a summary level and storing it in a custom object, you can reduce data storage and still provide visibility to the Sales Reps on how much money each customer generates year-over-year. Option A is not correct because storing data in a zip file does not make it available in Salesforce. Option C is not correct because exporting and deleting orders and order line items may lose important details that are needed for analysis or reporting. Option D is not correct because deleting orders and order line items without exporting them may cause data loss or inconsistency if the customer does not have order information in another system.

 According to the Salesforce documentation1, ownership skew occurs when a large number of records (more than 10,000) are owned by a single user or queue. This can cause performance issues and lock contention when multiple users try to access or update those records. To prevent ownership skew, some of the recommended practices are:

Assign a default user as the owner of the records and do not assign any role to the default user (option C). This way, the records will not be visible to other users in the role hierarchy and will not cause sharing recalculations.

Keep users out of public groups that can be used as the source for sharing rules (option B). Sharing rules based on public groups can cause excessive sharing calculations and lock contention when many records are owned by a single user or queue.

Assign a default user as the owner of the records and assign the top most role in the hierarchy to the default user (option E). This way, the records will be visible to all users in the role hierarchy, but will not cause sharing recalculations or lock contention.

Assigning a default user as the owner of the records and assigning a role in the hierarchy (option A) is not a good practice, as it can cause sharing recalculations and lock contention when the role is updated or moved. Assigning “view all” permission on profile to give access to the records (option D) is also not a good practice, as it can bypass the security and sharing model and expose sensitive data to unauthorized users.

According to the exam guide, one of the objectives is to "describe the use cases and considerations for deferring sharing calculations"1. This implies that option A is the correct way to load large amounts of data into Salesforce without affecting performance and data integrity. Deferring sharing calculations allows the data to be loaded first and then the sharing rules to be applied later2. Option B is not correct because workflows are not recommended for calculating summary values, as they can cause performance issues and data skew3. Option C is not correct because triggers are also not recommended for calculating summary values, as they can cause governor limit errors and data inconsistency. Option D is not correct because external IDs are used to link records from different systems, not to improve data loading performance.

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.

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.

A master data management (MDM) strategy for customer data can help UC ensure that all systems have access to the same customer information, without loading or duplicating data in all systems. An MDM strategy can also help UC avoid data conflicts and inconsistencies that may arise from having multiple systems as owners of data.

Before replicating the data from Heroku Postgres to Salesforce, the data architect should consider the following factors:

Whether the data is a driver of key processes implemented within Salesforce. For example, if the data is used for workflows, triggers, or validation rules, it should be replicated to Salesforce.

Whether there is a tight relationship between order data and an enterprise resource planning (ERP) application. For example, if the order data needs to be synchronized with the ERP system, it should be replicated to Salesforce.

The selection of the tool required to replicate the data. For example, Heroku Connect can be used to bi-directionally sync data between Heroku Postgres and Salesforce

Leveraging duplicate rules in Salesforce to validate duplicates during the account creation process (option A) is the best option to implement to avoid duplicates, as it allows the sales associates to identify and merge duplicate accounts before they are saved. Developing an Apex class that searches for duplicates and removes them nightly (option B) is not a good option, as it may cause data loss or conflicts, and it does not prevent duplicates from being created in the first place. Implementing an MDM solution to validate the customer information before creating Salesforce (option C) is also not a good option, as it may introduce additional complexity and cost, and it does not address the issue of customers interacting with both the website and the store. Building a custom search functionality that allows sales associates to search for customer in real time upon visiting their retail stores (option D) is also not a good option, as it may not be reliable or user-friendly, and it does not leverage the existing Global Search feature.

Creating a Dashboard using Analytics Cloud that will allow the user to create ad-hoc lenses and drill down is a recommended solution for building data exploration dashboards in Salesforce. Analytics Cloud is a powerful data analysis tool that enables users to explore data using interactive dashboards, charts, graphs, and tables on any device. Users can also create lenses, which are ad-hoc data queries that can be saved and reused, and drill down into data details using filters and facets. Creating a Dashboard in an external reporting tool, exporting data to the tool, and adding link to the dashboard in Salesforce will not provide a seamless user experience and may require additional data integration and security considerations. Creating a Dashboard in an external reporting tool, exporting data to the tool, and embedding the dashboard in Salesforce using the Canval toolkit will not provide a native Salesforce solution and may require additional data integration and security considerations. Creating a standard Salesforce Dashboard and connecting it to reports with the appropriate filters will not allow the user to create ad-hoc lenses and drill down into data details on their mobile device.

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.

The best API for retrieving Salesforce org metadata programmatically is the Metadata API. The Metadata API provides access to the metadata that defines the structure and configuration of an org, such as custom objects, fields, workflows, security settings, etc. It also supports deploying, retrieving, creating, updating, and deleting metadata components. The Metadata API can be used with various tools, such as Ant, Workbench, or IDEs.

  IP restrictions can be used to prevent users from accessing Salesforce from outside the company network or VPN. According to this article, sharing settings can be used to control access to customer information based on record ownership. According to this article, custom Apex can be used to support customer requests for removal of their information from Salesforce.

Having each system pull the record changes from Salesforce using change data capture (option D) is the correct solution for ensuring all systems using customer data are kept up to date, as it allows the systems to subscribe to real-time events from Salesforce and receive notifications when customer records are created, updated, deleted, or undeleted. Sending customer data nightly to the system of truth in a scheduled batch job (option A) or sending customer record changes from Salesforce to each system in a nightly batch job (option B) are not good solutions, as they may cause data latency and inconsistency, and they do not provide real-time updates. Sending customer record changes from Salesforce to the system of truth in real time (option C) is also not a good solution, as it does not address how the other systems will receive the updates from the system of truth.

 Making sure the query does not contain NULL in any filter criteria can avoid full table scans and leverage indexes more efficiently. Queries with NULL filters are not selective and can cause performance issues. Creating custom indexes on the fields used in the filter criteria can also enhance the query performance by reducing the number of records to scan.

 Engaging with executive sponsorship to assess enterprise data strategy and goals, and engaging with business units and IT to assess current operational systems and data models are two first steps that would be appropriate for UC to initiate an assessment of data architecture. These steps will help to understand the current state of data management, the business needs and expectations, and the gaps and opportunities for improvement. Engaging with IT program managers to assess current velocity of projects in the pipeline, and engaging with database administrators to assess current database performance metrics are not relevant steps for assessing data architecture, as they are more related to project management and technical performance.

Using external objects to maintain Sales Order in Salesforce is the best recommendation for maintaining Sales Orders in Salesforce, as it allows users to access large volumes of data stored outside Salesforce without copying or synchronizing it. Using custom objects, custom big objects, or standard order object may not be feasible or optimal for storing more than 150 million records that will not be updated in Salesforce.

Service Cloud License (option C) is the license type that UC users need to fulfill UC’s requirements, as it allows them to track customer complaints, provide white papers on products, and provide subscription-based support. Sales Cloud License (option A) is mainly for managing sales processes and leads, Lightning Platform Starter License (option B) is for building custom apps and workflows, and Salesforce License (option D) is a generic term that does not specify a particular license type.